Research Fellow / Senior Research Fellow at the intersection of machine learning and robotics
We are looking for a Research Fellow / Senior Research Fellow at the intersection of robotics and machine learning.
We are looking for a (Senior) Research Fellow at the intersection of robotics and machine learning.
Autonomous robots will play an increasingly important role in the future, e.g., in the context of healthcare, space exploration, or supporting humans in day-to-day activities. Key challenges, autonomous robots face are that they need to be able to learn from data and adapt fast to new situations without strong human interventions. Currently, autonomous learning systems either require vast amounts of data or they require human guidance. This project centers around approaches for data-efficient autonomous learning for robotics, e.g., by means of probabilistic modeling, transfer learning or using generic priors that constrain the learning system.
You will be part of the Statistical Machine Learning Group, which is located at UCL's Centre for Artificial Intelligence. We have a strong background in probabilistic modeling, data-efficient machine learning, and reinforcement learning. The successful applicant will lead and contribute to research projects at the intersection of statistical machine learning and climate science. They are also expected to contribute to student supervision and interact with research and project partners. The key objective is to design and evaluate machine learning approaches to advance the current state of the art in robot learning.
The post is graded as Grade 7 or Grade 8, with starting salary in the range £35,965 to £43,470 (Grade 7) or £44,674 to £52,701 (Grade 8) per annum (including London Allowance). Progression through the salary scale is incremental.
The funding for this post is for 24 months in the first instance.
The successful applicant will have a PhD (or close to be obtaining a PhD) in machine learning, statistics, computer science, robotics or a relevant area. They should have a track record of internationally recognized research and be able to work as part of a team. Research skills (theoretical and empirical, planning and documentary) plus effective written and verbal communication skills are essential.
More details and a link to the application can be found at
Please contact me if you have questions: m.deisenroth@ucl.ac.uk
I will also be at NeurIPS this month, and I'm happy to discuss opportunities in person.
✔️ @ApplyTime
We are looking for a Research Fellow / Senior Research Fellow at the intersection of robotics and machine learning.
We are looking for a (Senior) Research Fellow at the intersection of robotics and machine learning.
Autonomous robots will play an increasingly important role in the future, e.g., in the context of healthcare, space exploration, or supporting humans in day-to-day activities. Key challenges, autonomous robots face are that they need to be able to learn from data and adapt fast to new situations without strong human interventions. Currently, autonomous learning systems either require vast amounts of data or they require human guidance. This project centers around approaches for data-efficient autonomous learning for robotics, e.g., by means of probabilistic modeling, transfer learning or using generic priors that constrain the learning system.
You will be part of the Statistical Machine Learning Group, which is located at UCL's Centre for Artificial Intelligence. We have a strong background in probabilistic modeling, data-efficient machine learning, and reinforcement learning. The successful applicant will lead and contribute to research projects at the intersection of statistical machine learning and climate science. They are also expected to contribute to student supervision and interact with research and project partners. The key objective is to design and evaluate machine learning approaches to advance the current state of the art in robot learning.
The post is graded as Grade 7 or Grade 8, with starting salary in the range £35,965 to £43,470 (Grade 7) or £44,674 to £52,701 (Grade 8) per annum (including London Allowance). Progression through the salary scale is incremental.
The funding for this post is for 24 months in the first instance.
The successful applicant will have a PhD (or close to be obtaining a PhD) in machine learning, statistics, computer science, robotics or a relevant area. They should have a track record of internationally recognized research and be able to work as part of a team. Research skills (theoretical and empirical, planning and documentary) plus effective written and verbal communication skills are essential.
More details and a link to the application can be found at
Please contact me if you have questions: m.deisenroth@ucl.ac.uk
I will also be at NeurIPS this month, and I'm happy to discuss opportunities in person.
✔️ @ApplyTime
Two postdoctoral positions are available in the lab of Carlos Fernandez-Granda at the Courant Institute and Center for Data Science at NYU:
- Machine learning for healthcare: The focus is the design of deep-learning methodology for medical applications, with emphasis on domain adaptation, high-dimensional signal processing, and semi-supervised learning. The developed techniques will be applied to automatic quantification of rehabilitation dose in stroke patients from sensor and camera data, in collaboration with the Mobilis Lab in the Department of Neurology at NYU School of Medicine, which aims to enhance motor recovery after stroke.
Link: https://apply.interfolio.com/66997
- Machine learning for dynamical systems: The focus is the design of machine-learning methodology for the analysis of dynamic systems, with potential applications to computer vision, material science and molecular biology.
Link: https://apply.interfolio.com/69741
Qualifications
Candidates should possess a Ph.D. in Computer Science, Electrical Engineering, Data Science, or related disciplines. In addition, they should have a strong background in machine learning, and solid programming skills. They must have the ability to work independently and with an interdisciplinary team.
Application Instructions
Interested candidates should submit (1) a CV, (2) a brief cover letter explaining their research experience, how their interests would fit the goals of the project, career plans, and available start date, and (3) the names and contact information of three references familiar with the applicant’s research and academic work.
✔️ @ApplyTime
- Machine learning for healthcare: The focus is the design of deep-learning methodology for medical applications, with emphasis on domain adaptation, high-dimensional signal processing, and semi-supervised learning. The developed techniques will be applied to automatic quantification of rehabilitation dose in stroke patients from sensor and camera data, in collaboration with the Mobilis Lab in the Department of Neurology at NYU School of Medicine, which aims to enhance motor recovery after stroke.
Link: https://apply.interfolio.com/66997
- Machine learning for dynamical systems: The focus is the design of machine-learning methodology for the analysis of dynamic systems, with potential applications to computer vision, material science and molecular biology.
Link: https://apply.interfolio.com/69741
Qualifications
Candidates should possess a Ph.D. in Computer Science, Electrical Engineering, Data Science, or related disciplines. In addition, they should have a strong background in machine learning, and solid programming skills. They must have the ability to work independently and with an interdisciplinary team.
Application Instructions
Interested candidates should submit (1) a CV, (2) a brief cover letter explaining their research experience, how their interests would fit the goals of the project, career plans, and available start date, and (3) the names and contact information of three references familiar with the applicant’s research and academic work.
✔️ @ApplyTime
Research Associate Water Chemistry
Technische Universität Dresden
At the TU Dresden, faculty of Environmental Sciences, Department of Hydro Sciences, the Institute of Water Chemistry offers, as soon as possible, a position as
Research Associate
(Subject to personal qualification employees are remunerated according to salary group E 13 TV-L)
lasting to the end of the project on 31.12.2022 which entails 65 % of the fulltime weekly hours. The period of employment is governed by the Fixed Term Research Contracts Act (Wissenschaftszeit-vertragsgesetz - WissZeitVG). The position offers the chance to obtain further academic qualification (e.g. PhD).
Within the framework of an ESF funded junior research group, it is the aim to develop a system for peptide-based cell-cell communication between yeasts and bacteria for technological processes. A priority objective shall be the comprehensive elucidation of control mechanisms, which are necessary for a balanced cultivation of microbial communities and the optimal exchange of metabolites, in order to enable a conscious use of those mechanisms.
Activities and responsibilities
Establishing analytical methods for the quantification of signal peptides (pheromones) using HPLC-MS/MS and modification thereof in order to meet the needs of more complex matrices and low concentrations, including pre-analytical approaches like SPE, GPC/SEC or ultrafiltration; furthermore, the quantitative determination of selected antibiotics in water and culture media samples, the deduction of kinetic data concerning the biochemical degradation of antibiotics and the characterisation of transformation products.
Qualification profile
Junior researcher, a very good university degree in the fields of chemistry, biochemistry, food chemistry, environmental sciences or similar, obtained no longer than 4 years ago (plus e.g. times of parental leave); a high level of motivation and interest in scientific and interdisciplinary research; very good knowledge of English language (written and spoken); ability to work independently and well-structured in a team with a high level of communication and cooperation within the junior research group; analytical thinking; exceptional skills in laboratory work as well as a deep understanding within the field of analytical chemistry (especially determination of peptides and antibiotics using HPLC-MS/MS, sample preparation), hydrochemistry, biochemistry and microbiology.
Send application to
Please, send your expressive application including all common documents by 09.01.2020 (stamped arrival date of the university central mail service applies) to TU Dresden, Fakultät Umweltwissenschaften, Fachrichtung Hydrowissenschaften, Institut für Wasserchemie, Herrn Prof. Dr. Stefan Stolte, Helmholtzstr. 10, 01069 Dresden. Please submit copies only, as your application will not be returned to you. Expenses incurred in attending interviews cannot be reimbursed.
Reference to data protection: Your data protection rights, the purpose for which your data will be processed, as well as further information about data protection is available to you on the website: https://tu-dresden.de/karriere/datenschutzhinweis
✔️ @ApplyTime
Technische Universität Dresden
At the TU Dresden, faculty of Environmental Sciences, Department of Hydro Sciences, the Institute of Water Chemistry offers, as soon as possible, a position as
Research Associate
(Subject to personal qualification employees are remunerated according to salary group E 13 TV-L)
lasting to the end of the project on 31.12.2022 which entails 65 % of the fulltime weekly hours. The period of employment is governed by the Fixed Term Research Contracts Act (Wissenschaftszeit-vertragsgesetz - WissZeitVG). The position offers the chance to obtain further academic qualification (e.g. PhD).
Within the framework of an ESF funded junior research group, it is the aim to develop a system for peptide-based cell-cell communication between yeasts and bacteria for technological processes. A priority objective shall be the comprehensive elucidation of control mechanisms, which are necessary for a balanced cultivation of microbial communities and the optimal exchange of metabolites, in order to enable a conscious use of those mechanisms.
Activities and responsibilities
Establishing analytical methods for the quantification of signal peptides (pheromones) using HPLC-MS/MS and modification thereof in order to meet the needs of more complex matrices and low concentrations, including pre-analytical approaches like SPE, GPC/SEC or ultrafiltration; furthermore, the quantitative determination of selected antibiotics in water and culture media samples, the deduction of kinetic data concerning the biochemical degradation of antibiotics and the characterisation of transformation products.
Qualification profile
Junior researcher, a very good university degree in the fields of chemistry, biochemistry, food chemistry, environmental sciences or similar, obtained no longer than 4 years ago (plus e.g. times of parental leave); a high level of motivation and interest in scientific and interdisciplinary research; very good knowledge of English language (written and spoken); ability to work independently and well-structured in a team with a high level of communication and cooperation within the junior research group; analytical thinking; exceptional skills in laboratory work as well as a deep understanding within the field of analytical chemistry (especially determination of peptides and antibiotics using HPLC-MS/MS, sample preparation), hydrochemistry, biochemistry and microbiology.
Send application to
Please, send your expressive application including all common documents by 09.01.2020 (stamped arrival date of the university central mail service applies) to TU Dresden, Fakultät Umweltwissenschaften, Fachrichtung Hydrowissenschaften, Institut für Wasserchemie, Herrn Prof. Dr. Stefan Stolte, Helmholtzstr. 10, 01069 Dresden. Please submit copies only, as your application will not be returned to you. Expenses incurred in attending interviews cannot be reimbursed.
Reference to data protection: Your data protection rights, the purpose for which your data will be processed, as well as further information about data protection is available to you on the website: https://tu-dresden.de/karriere/datenschutzhinweis
✔️ @ApplyTime
TU Dresden
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Call for Visiting Fellows, Spring Term 2020 - DEADLINE 10 January
The National Center of Competence in Research nccr – on the move aims to enhance the understanding of contemporary phenomena related to migration and mobility in Switzerland and beyond. Connecting disciplines, the NCCR brings together research projects from the social sciences, economics and law. Managed from the University of Neuchâtel, the network comprises ten universities in Switzerland.
Short-Term Visiting Fellowships
The nccr – on the move wishes to encourage its network members to connect with research teams abroad. We are therefore setting up short-term visiting fellowships that are available to both incoming and outgoing fellows. The grants are explicitly not a salary: instead, they are meant to cover travel, room and board expenses during the stay in Switzerland (for incoming fellows) or abroad (for outcoming fellows).
The “incoming” fellowship scheme can be used to host senior (PostDoc) and junior (doctoral) researchers from abroad who wish to collaborate with nccr – on the move in Switzerland for a duration of two to three months. The monthly installment is based on a lump-sum amount for staying in Switzerland, which amounts to CHF 3000 per month for applicants from developed countries and CHF 3500 for applicants from developing countries. In addition, one roundtrip from the place of residence to the host university is paid. Travel related to nccr – on the move events in Switzerland is reimbursed upon presentation of receipts.
The “outgoing” fellowship scheme is aimed at nccr – on the move PostDocs and doctoral students who wish to go abroad for a maximum of five months. The NCCR contributes a maximum amount of CHF 10,000 towards the stay abroad,
whereby the maximum monthly installment is set at CHF 3,000. In addition, the grant covers the cost of an outward and return journey to the host institution. We ask the nccr – on the move fellows seeking to go abroad for six months or more to apply for the official SNSF NCCR Mobility Grants, which have been created for NCCR collaborators wishing to go abroad. The Network Office can provide you with the documentation, further information and assistance in applying for these grants.
During the visit, both the incoming and the outgoing fellows pursue a small joint research project in collaboration with the team hosting them. Research projects can either be joint submissions, the preparation and/or realization of a workshop or a collaborative publication. In the framework of the “incoming” fellowships the academic guests shall participate in the nccr – on the move activities.
Based on the present call, a maximum of four fellowships will be awarded by the Scientific Committee of the nccr – on the move in January 2020.
You can find information on the nccr – on the move, the focus of the research and the individual projects on our website.
More information here.
✔️ @ApplyTime
The National Center of Competence in Research nccr – on the move aims to enhance the understanding of contemporary phenomena related to migration and mobility in Switzerland and beyond. Connecting disciplines, the NCCR brings together research projects from the social sciences, economics and law. Managed from the University of Neuchâtel, the network comprises ten universities in Switzerland.
Short-Term Visiting Fellowships
The nccr – on the move wishes to encourage its network members to connect with research teams abroad. We are therefore setting up short-term visiting fellowships that are available to both incoming and outgoing fellows. The grants are explicitly not a salary: instead, they are meant to cover travel, room and board expenses during the stay in Switzerland (for incoming fellows) or abroad (for outcoming fellows).
The “incoming” fellowship scheme can be used to host senior (PostDoc) and junior (doctoral) researchers from abroad who wish to collaborate with nccr – on the move in Switzerland for a duration of two to three months. The monthly installment is based on a lump-sum amount for staying in Switzerland, which amounts to CHF 3000 per month for applicants from developed countries and CHF 3500 for applicants from developing countries. In addition, one roundtrip from the place of residence to the host university is paid. Travel related to nccr – on the move events in Switzerland is reimbursed upon presentation of receipts.
The “outgoing” fellowship scheme is aimed at nccr – on the move PostDocs and doctoral students who wish to go abroad for a maximum of five months. The NCCR contributes a maximum amount of CHF 10,000 towards the stay abroad,
whereby the maximum monthly installment is set at CHF 3,000. In addition, the grant covers the cost of an outward and return journey to the host institution. We ask the nccr – on the move fellows seeking to go abroad for six months or more to apply for the official SNSF NCCR Mobility Grants, which have been created for NCCR collaborators wishing to go abroad. The Network Office can provide you with the documentation, further information and assistance in applying for these grants.
During the visit, both the incoming and the outgoing fellows pursue a small joint research project in collaboration with the team hosting them. Research projects can either be joint submissions, the preparation and/or realization of a workshop or a collaborative publication. In the framework of the “incoming” fellowships the academic guests shall participate in the nccr – on the move activities.
Based on the present call, a maximum of four fellowships will be awarded by the Scientific Committee of the nccr – on the move in January 2020.
You can find information on the nccr – on the move, the focus of the research and the individual projects on our website.
More information here.
✔️ @ApplyTime
Funded Research Assistantship @ Poetic Justice Group MIT Media Lab
The Poetic Justice Group (PJG) at MIT Media Lab, founded by artist Ekene Ijeoma, is accepting applications for their two-year funded (tuition, medical insurance, and a stipend) research assistantship and graduate student program.
The Poetic Justice group is looking for thinkers and makers who feel the urgency to break down the complexities of social issues and build visibility, accountability, and solidarity around them. Applicants should already be thinking critically about their disciplines and continually searching for cross-disciplinary connections. Although not required, we’re particularly interested in applicants with professional experience.
PJG is a group of critical thinkers and makers who are exploring new forms of justice through art. We question, if “Artists need to create on the same scale as society has the capacity to destroy,” as Sherrie Rabinowitz suggested in 1984, then how can social justice be expanded through conceptual art informed by computational and architectural design strategies? As some mediums are better for some messages than others, we question what new media should be used for these new forms of social justice. If a new form of social justice is searching for our truths, how can we find them at the intersections of oral histories and data studies? How can we create artworks which engage with and furthermore embody these truths? How can these artworks extend our perceptions and expose the social-political systems affecting our truths? How can the forms of these artworks function at the intersections of poetic acts and analytic insights as well as aesthetic quality and social efficacy?
We’re exploring these questions through ongoing projects which include A Counting, The Green Book Project and The Scream Project. 'A Counting’ is a site-specific multimedia artwork that counts from 1 to 100; playing different crowdsourced multilingual voice samples for every number and displaying the word in the language. The Green Book Project is a series of courses, workshops, publications and interactive installations that reimagine the Negro Motorist Green Book for “traveling while Black” in this era of “New Jim Crows.” And the Scream Project is a series of publications and interactive installations that revive the Teotihuacan folklore/ritual of women practicing catharsis in the pyramids to contemporary urban spaces.
Applications are due December 1st. You can read more about our research group here and the graduate program here.
✔️ @ApplyTime
The Poetic Justice Group (PJG) at MIT Media Lab, founded by artist Ekene Ijeoma, is accepting applications for their two-year funded (tuition, medical insurance, and a stipend) research assistantship and graduate student program.
The Poetic Justice group is looking for thinkers and makers who feel the urgency to break down the complexities of social issues and build visibility, accountability, and solidarity around them. Applicants should already be thinking critically about their disciplines and continually searching for cross-disciplinary connections. Although not required, we’re particularly interested in applicants with professional experience.
PJG is a group of critical thinkers and makers who are exploring new forms of justice through art. We question, if “Artists need to create on the same scale as society has the capacity to destroy,” as Sherrie Rabinowitz suggested in 1984, then how can social justice be expanded through conceptual art informed by computational and architectural design strategies? As some mediums are better for some messages than others, we question what new media should be used for these new forms of social justice. If a new form of social justice is searching for our truths, how can we find them at the intersections of oral histories and data studies? How can we create artworks which engage with and furthermore embody these truths? How can these artworks extend our perceptions and expose the social-political systems affecting our truths? How can the forms of these artworks function at the intersections of poetic acts and analytic insights as well as aesthetic quality and social efficacy?
We’re exploring these questions through ongoing projects which include A Counting, The Green Book Project and The Scream Project. 'A Counting’ is a site-specific multimedia artwork that counts from 1 to 100; playing different crowdsourced multilingual voice samples for every number and displaying the word in the language. The Green Book Project is a series of courses, workshops, publications and interactive installations that reimagine the Negro Motorist Green Book for “traveling while Black” in this era of “New Jim Crows.” And the Scream Project is a series of publications and interactive installations that revive the Teotihuacan folklore/ritual of women practicing catharsis in the pyramids to contemporary urban spaces.
Applications are due December 1st. You can read more about our research group here and the graduate program here.
✔️ @ApplyTime
MIT Media Lab
Group Overview ‹ Poetic Justice – MIT Media Lab
Exploring new forms of social justice through art
Amazon Alexa Shopping in London/Cambridge is hiring Applied Scientists and Applied Science Interns!
You: Alexa, I am looking for a new career opportunity! I want to do exciting and innovative work in AI and impact millions of people. What do you suggest?
Alexa: The Alexa Shopping team is looking for Applied Scientists to help me become the best personal shopping assistant. Do you want to hear more?
You: Yes, please!
The Alexa Shopping team in the UK is looking for both applied scientists and applied science interns (for summer 2020) investigating and developing machine learning and privacy enhancing technologies to help Alexa turn into the best and most trustworthy personal shopping assistant.
The ideal candidate has expertise in one or several of the following fields: Machine Learning, Applied/Theoretical Statistics, Crowdsourcing, Differential Privacy, Algorithmic Fairness. S/he also shows good intuition with the technologies behind personal assistants and the needs of customers. The ability to write clearly and speak convincingly as evidenced through participation in academic conferences and service in the scientific community are a must.
Applied Scientist: https://www.amazon.jobs/en/jobs/979175/applied-scientist
Applied Science Internships: https://www.amazon.jobs/en/jobs/1003772/2020-machine-learning-internship-alexa-shopping
Amazon is an Equal Opportunity-Affirmative Action Employer – Minority/Female/Disability/Veteran/Gender Identity/Sexual Orientation
For more information about the position, please contact Tom Diethe (tdiethe@amazon.com) or Andreas Damianou (damianou@amazon.com)
✔️ @ApplyTime
You: Alexa, I am looking for a new career opportunity! I want to do exciting and innovative work in AI and impact millions of people. What do you suggest?
Alexa: The Alexa Shopping team is looking for Applied Scientists to help me become the best personal shopping assistant. Do you want to hear more?
You: Yes, please!
The Alexa Shopping team in the UK is looking for both applied scientists and applied science interns (for summer 2020) investigating and developing machine learning and privacy enhancing technologies to help Alexa turn into the best and most trustworthy personal shopping assistant.
The ideal candidate has expertise in one or several of the following fields: Machine Learning, Applied/Theoretical Statistics, Crowdsourcing, Differential Privacy, Algorithmic Fairness. S/he also shows good intuition with the technologies behind personal assistants and the needs of customers. The ability to write clearly and speak convincingly as evidenced through participation in academic conferences and service in the scientific community are a must.
Applied Scientist: https://www.amazon.jobs/en/jobs/979175/applied-scientist
Applied Science Internships: https://www.amazon.jobs/en/jobs/1003772/2020-machine-learning-internship-alexa-shopping
Amazon is an Equal Opportunity-Affirmative Action Employer – Minority/Female/Disability/Veteran/Gender Identity/Sexual Orientation
For more information about the position, please contact Tom Diethe (tdiethe@amazon.com) or Andreas Damianou (damianou@amazon.com)
✔️ @ApplyTime
amazon.jobs
Applied Scientist
You: Alexa, I am looking for a new impactful role where I could tackle the next big research challenge in search, what do you suggest?Alexa: The Alexa Shopping team is looking for applied research leaders to help me become the best personal shopping assistant.…
Two Studentships in Gerontology - DEADLINE 23 January
A fully funded studentship awarded by the Economic and Social Research Council (ESRC) South Coast Doctoral Training Partnership (SCDTP) commencing in 2020/21 Academic Year.
Supervisory Team
Prof. Athina Vlachantoni and Prof. Maria Evandrou (both in Department of Gerontology, Centre for Population Change and Centre for Research on Ageing, University of Southampton)
Older persons from minority ethnic communities in the UK have been shown to be at a financial disadvantage compared to the White British population, however there remain questions about the role of pensions in ethnic elders’ income and the ways in which they prepare financially for later life. The project will combine analysis of the UK Household Longitudinal Survey with semi-structured interviews with older individuals from Indian, Pakistani and Bangladeshi communities in the UK, in order to explore the composition of ethnic elders’ income, the role of pensions in such income, and alternative (non-pension) strategies for financial adequacy in later life.
Skills Required
Essential: Background in a social sciences subject, ideally linked to ethnicity and/ or ageing over the life course; Knowledge of logistic regression modelling; Knowledge of qualitative interviewing. Desirable: Knowledge of mixed methods research; experience in using USoc or other large-scale datasets.
More info
✔️ @ApplyTime
A fully funded studentship awarded by the Economic and Social Research Council (ESRC) South Coast Doctoral Training Partnership (SCDTP) commencing in 2020/21 Academic Year.
Supervisory Team
Prof. Athina Vlachantoni and Prof. Maria Evandrou (both in Department of Gerontology, Centre for Population Change and Centre for Research on Ageing, University of Southampton)
Older persons from minority ethnic communities in the UK have been shown to be at a financial disadvantage compared to the White British population, however there remain questions about the role of pensions in ethnic elders’ income and the ways in which they prepare financially for later life. The project will combine analysis of the UK Household Longitudinal Survey with semi-structured interviews with older individuals from Indian, Pakistani and Bangladeshi communities in the UK, in order to explore the composition of ethnic elders’ income, the role of pensions in such income, and alternative (non-pension) strategies for financial adequacy in later life.
Skills Required
Essential: Background in a social sciences subject, ideally linked to ethnicity and/ or ageing over the life course; Knowledge of logistic regression modelling; Knowledge of qualitative interviewing. Desirable: Knowledge of mixed methods research; experience in using USoc or other large-scale datasets.
More info
✔️ @ApplyTime
South Coast Doctoral Training Partnership
Apply - South Coast Doctoral Training Partnership
Our call for applications for studentships commencing in 2026/27 is now open (from 26th January 2025, 12:00am) The deadline for application is 16:00 GMT 16th Jan 2026. Below are our current application procedures Application Procedure The application…
Apply Time Positions pinned «#ApplyTime از زمانی که کانال #اپلای تایم راهاندازی شده است، اندکی بیش از 3 سال میگذرد! شاید باور کردنش دشوار باشد، ولی در طول این 3 سال بیش از 5000 موقعیت و یا بورسیهی تحصیلی در مقاطع گوناگون، رشتههای متنوع، و کشورهای مختلف با شما به اشتراک گذارده شده…»
Dr. Mahdi Imani, an assistant professor at the Department of Electrical and Computer Engineering at the George Washington University, seeks for multiple PhD students with interests in Machine Learning, Reinforcement Learning and Statistics. Ideal candidates may have:
- Master’s degree in electrical/computer engineering or computer science.
- Strong background in mathematics and statistics.
- Good programming skills (e.g., Python).
Prospective students may email their CV, trannoscripts and English test scores at imani.gwu@gmail.com. For more information, see https://web.seas.gwu.edu/imani/.
Self-supported postdoctoral and visiting scholars are encouraged to contact as well.
--
Mahdi Imani, Ph.D.
Assistant Professor
Dept. of Electrical and Computer Eng.
George Washington University
https://web.seas.gwu.edu/imani/
✔️ @ApplyTime
- Master’s degree in electrical/computer engineering or computer science.
- Strong background in mathematics and statistics.
- Good programming skills (e.g., Python).
Prospective students may email their CV, trannoscripts and English test scores at imani.gwu@gmail.com. For more information, see https://web.seas.gwu.edu/imani/.
Self-supported postdoctoral and visiting scholars are encouraged to contact as well.
--
Mahdi Imani, Ph.D.
Assistant Professor
Dept. of Electrical and Computer Eng.
George Washington University
https://web.seas.gwu.edu/imani/
✔️ @ApplyTime
PostDoc Researcher at Accenture Labs Dublin - Graph Representation Learning and Explainable AI
Accenture Labs Dublin is looking for a Post-Doctoral researcher in the domain of Graph Representation Learning and Explainable AI.
You will join a newly-created, multi-partner project whose goal is to identify factors that can cause development of new medical conditions, and worsen the quality of life of cancer survivors. The project will analyse patient’s clinical, genomic, behavioural data and existing open data in order to determine a follow-up adapted to the individual needs. The length of the PostDoc is 3 years.
You will join our team of AI researchers and engineers, and work on research activities focused on explainable AI and machine learning on knowledge graphs.
You will be in charge of designing, developing, evaluating, and applying novel models. That will include software development (including contributing to our open source stack [1]), carrying out experiments, and publishing results in academic venues.
More precisely, you will design interpretable machine learning models to infer knowledge from a graph of clinical, genomic, and behavioural data. Explanations will use a wide range of techniques, such as rules derived from the deep learning models, interpretable machine learning, or graph-based explanations based on network analysis.
Requirements
* PhD in computer science, statistics, mathematics or related field.
* Proven communication skills (talks, presentations, academic publications)
* Strong foundation in mathematics, statistics and probability
* Strong knowledge of Machine Learning foundations
* Knowledge of mainstream Deep Learning architectures
* Ability to work creatively and analytically in a problem-solving environment
* Strong Python programming skills
* Hands-on experience with machine learning frameworks (e.g. TensorFlow, PyTorch), and scientific Python (e.g. numpy)
* Eagerness to contribute in a team-oriented environment
Preferred Qualifications
* Experience with graph-based knowledge representation (e.g. knowledge graphs)
* Familiarity with graph representation learning (e.g. knowledge graph embeddings, graph neural networks)
* Experience with explainable AI or interpretable machine learning techniques
* Working knowledge of Linux OS and shell noscripting
* Hands-on experience with git and issue tracking systems
About Accenture Labs Dublin
Accenture Labs is a network of R&D labs distributed on seven locations worldwide, home of over 200 applied R&D experts. The Dublin Labs team focuses on artificial intelligence, with a strong emphasis on explainable AI, machine learning on knowledge graphs (graph representation learning), and computational creativity. The lab is co-located with the over 100 designers, developers and domain experts at The Dock, Accenture's newly-created global centre for innovation.
We offer a blend of industrial-related applicative problems and academic-oriented activities, including an open publication policy.
Apply online here:
https://www.accenture.com/ie-en/careers/jobdetails?id=00784132_en
or feel free to contact Luca Costabello should you have any questions [2].
[1] https://github.com/Accenture/AmpliGraph
[2] https://luca.costabello.info/
✔️ @ApplyTime
Accenture Labs Dublin is looking for a Post-Doctoral researcher in the domain of Graph Representation Learning and Explainable AI.
You will join a newly-created, multi-partner project whose goal is to identify factors that can cause development of new medical conditions, and worsen the quality of life of cancer survivors. The project will analyse patient’s clinical, genomic, behavioural data and existing open data in order to determine a follow-up adapted to the individual needs. The length of the PostDoc is 3 years.
You will join our team of AI researchers and engineers, and work on research activities focused on explainable AI and machine learning on knowledge graphs.
You will be in charge of designing, developing, evaluating, and applying novel models. That will include software development (including contributing to our open source stack [1]), carrying out experiments, and publishing results in academic venues.
More precisely, you will design interpretable machine learning models to infer knowledge from a graph of clinical, genomic, and behavioural data. Explanations will use a wide range of techniques, such as rules derived from the deep learning models, interpretable machine learning, or graph-based explanations based on network analysis.
Requirements
* PhD in computer science, statistics, mathematics or related field.
* Proven communication skills (talks, presentations, academic publications)
* Strong foundation in mathematics, statistics and probability
* Strong knowledge of Machine Learning foundations
* Knowledge of mainstream Deep Learning architectures
* Ability to work creatively and analytically in a problem-solving environment
* Strong Python programming skills
* Hands-on experience with machine learning frameworks (e.g. TensorFlow, PyTorch), and scientific Python (e.g. numpy)
* Eagerness to contribute in a team-oriented environment
Preferred Qualifications
* Experience with graph-based knowledge representation (e.g. knowledge graphs)
* Familiarity with graph representation learning (e.g. knowledge graph embeddings, graph neural networks)
* Experience with explainable AI or interpretable machine learning techniques
* Working knowledge of Linux OS and shell noscripting
* Hands-on experience with git and issue tracking systems
About Accenture Labs Dublin
Accenture Labs is a network of R&D labs distributed on seven locations worldwide, home of over 200 applied R&D experts. The Dublin Labs team focuses on artificial intelligence, with a strong emphasis on explainable AI, machine learning on knowledge graphs (graph representation learning), and computational creativity. The lab is co-located with the over 100 designers, developers and domain experts at The Dock, Accenture's newly-created global centre for innovation.
We offer a blend of industrial-related applicative problems and academic-oriented activities, including an open publication policy.
Apply online here:
https://www.accenture.com/ie-en/careers/jobdetails?id=00784132_en
or feel free to contact Luca Costabello should you have any questions [2].
[1] https://github.com/Accenture/AmpliGraph
[2] https://luca.costabello.info/
✔️ @ApplyTime
Accenture
PostDoc Researcher - Graph Representation Learning and Explainable AI
Learn more about applying for PostDoc Researcher - Graph Representation Learning and Explainable AI position at Accenture.
Postdoc position in computational biology/bioinformatics
at the Department of Genomics & Immunoregulation at the Life & Medical Sciences (LIMES) Institute, starting in December 2019 for two years, with the possibility of extension, in the field of single cell trannoscriptome analysis.
The LIMES (Life and Medical Sciences) Institute is part of the Faculty of Mathematical and Natural Sciences at the University of Bonn. The Institute has been established to foster molecular research spanning from immunology to metabolism using a broad spectrum of cutting-edge technologies including state-of–the-art genomic technologies. In this regard, the Department for Genomics and Immunoregulation at the LIMES-Institute together with PRECISE at the DZNE Bonn has a Next-Generation Sequencing Facility and is now seeking scientist in the field of bioinformatics, computational biology and systems biology with focus in single cell trannoscriptome analysis. The successful candidate will be part of a team preprocessing and analyzing single cell Next-Generation Sequencing data and improving/developing computational approaches using state of the art tools and IT infrastructure.
Our requirements are
Enthusiasm to work in a thriving academic research environment.
Strong background in computational biology, bioinformatics, biomathematics, biostatistics.
Experience in the analysis of Next-Generation Sequencing data e.g. single cell RNA-Seq, bulk RNA-Seq and ATAC/ChIP-Seq.
Strong background in biology, preferable immunology.
PhD degree or equivalent.
An interest to work in an international environment.
A collaborative attitude.
Ability to work independently as well as in a team.
Computer programming as well as skills.
Experience in working in Linux based environments.
Very good communication and writing skills in English.
What we have to offer
Challenging research projects.
State of the art technologies to tackle important scientific and medical questions
A thriving interdisciplinary research environment at the LIMES Institute.
Fully established bioinformatics department.
Salary is paid according to German TV-L (E 13 100%).
The University of Bonn is an equal opportunities employer.
Complete applications in English should include a CV, a brief statement of research experiences and interests, list of publications and addresses of two referees should be submitted as a single pdf file to Professor Dr. Joachim L. Schultze (office.immunogenomics@uni-bonn.de) by 22th of November.
✔️ @ApplyTime
at the Department of Genomics & Immunoregulation at the Life & Medical Sciences (LIMES) Institute, starting in December 2019 for two years, with the possibility of extension, in the field of single cell trannoscriptome analysis.
The LIMES (Life and Medical Sciences) Institute is part of the Faculty of Mathematical and Natural Sciences at the University of Bonn. The Institute has been established to foster molecular research spanning from immunology to metabolism using a broad spectrum of cutting-edge technologies including state-of–the-art genomic technologies. In this regard, the Department for Genomics and Immunoregulation at the LIMES-Institute together with PRECISE at the DZNE Bonn has a Next-Generation Sequencing Facility and is now seeking scientist in the field of bioinformatics, computational biology and systems biology with focus in single cell trannoscriptome analysis. The successful candidate will be part of a team preprocessing and analyzing single cell Next-Generation Sequencing data and improving/developing computational approaches using state of the art tools and IT infrastructure.
Our requirements are
Enthusiasm to work in a thriving academic research environment.
Strong background in computational biology, bioinformatics, biomathematics, biostatistics.
Experience in the analysis of Next-Generation Sequencing data e.g. single cell RNA-Seq, bulk RNA-Seq and ATAC/ChIP-Seq.
Strong background in biology, preferable immunology.
PhD degree or equivalent.
An interest to work in an international environment.
A collaborative attitude.
Ability to work independently as well as in a team.
Computer programming as well as skills.
Experience in working in Linux based environments.
Very good communication and writing skills in English.
What we have to offer
Challenging research projects.
State of the art technologies to tackle important scientific and medical questions
A thriving interdisciplinary research environment at the LIMES Institute.
Fully established bioinformatics department.
Salary is paid according to German TV-L (E 13 100%).
The University of Bonn is an equal opportunities employer.
Complete applications in English should include a CV, a brief statement of research experiences and interests, list of publications and addresses of two referees should be submitted as a single pdf file to Professor Dr. Joachim L. Schultze (office.immunogenomics@uni-bonn.de) by 22th of November.
✔️ @ApplyTime
PhD position - Microbial Biotechnology
Forschungszentrum Jülich GmbH Jülich
Your Job:
Many biotechnological processes fail because the product imposes too much stress on the microbe. We aim to address this by utilizing naturally stress-resistant Pseudomonas bacteria in a collaborative project called NO-STRESS. You will investigate microbial stress tolerance mechanisms. Based on your findings, you will engineer new strains with higher tolerance to chemical stressors. You will evaluate these new strains through biocatalytic production of industrially relevant chemicals, using state-of-the-art production pathways available in our lab. Your methodical focus will be on genetic engineering, metabolic engineering, and laboratory evolution.
More info
✔️ @ApplyTime
Forschungszentrum Jülich GmbH Jülich
Your Job:
Many biotechnological processes fail because the product imposes too much stress on the microbe. We aim to address this by utilizing naturally stress-resistant Pseudomonas bacteria in a collaborative project called NO-STRESS. You will investigate microbial stress tolerance mechanisms. Based on your findings, you will engineer new strains with higher tolerance to chemical stressors. You will evaluate these new strains through biocatalytic production of industrially relevant chemicals, using state-of-the-art production pathways available in our lab. Your methodical focus will be on genetic engineering, metabolic engineering, and laboratory evolution.
More info
✔️ @ApplyTime
www.fz-juelich.de
Forschungszentrum Jülich - Current Vacancies - PhD position - Microbial Biotechnology
post-doctoral fellowship is available for 2D/2.5D/3D/4D radiology image processing in Bethesda, Maryland, USA
Position Denoscription:
A post-doctoral fellowship is available for 2D/2.5D/3D/4D radiology image processing in Bethesda, Maryland, USA. Specific interest areas are deep learning, image segmentation, modeling, visualization, pattern recognition, computer-aided diagnosis, multi-organ models, atlases and registration. In particular, advanced skills in image processing (computer vision, mathematical modeling, optimization, machine learning) are sought. The researcher will work closely with staff scientists, imaging specialists and clinicians and have access to state-of-the-art whole body MRI, MRI-PET, low-dose CT scanners, advanced graphics workstations and parallel processing/GPU clusters.
For additional information, please visit: https://www.cc.nih.gov/meet-our-doctors/rsummers.html.
Qualifications:
Ph.D. in Computer Science, Electrical Engineering, or related discipline with experience in Computer Vision, Machine Learning, or Image Understanding domain, along with successful demonstration of key responsibilities.
Strong theoretical and practical background in computer vision, image and video analysis, such as object detection and recognition, statistical pattern recognition, machine learning, sparse methods and applied optimization. Prior knowledge about medical imaging is a plus but not a must. Enthusiasm in solving real world clinical imaging problems using large datasets, and hands-on coding skills and ability in C++ and Matlab.
This appointment is for one year and is renewable thereafter on a periodic basis (up to five years).
To Apply:
Applications should include a CV, brief statement of research interests and three letters of reference. Email application materials to Dr. Ronald Summers at rms@nih.gov.
DHHS and NIH are Equal Opportunity Employers.
Regards,
Sheeraz Akram
https://www.linkedin.com/in/sheerazakram/
More info
✔️ @ApplyTime
Position Denoscription:
A post-doctoral fellowship is available for 2D/2.5D/3D/4D radiology image processing in Bethesda, Maryland, USA. Specific interest areas are deep learning, image segmentation, modeling, visualization, pattern recognition, computer-aided diagnosis, multi-organ models, atlases and registration. In particular, advanced skills in image processing (computer vision, mathematical modeling, optimization, machine learning) are sought. The researcher will work closely with staff scientists, imaging specialists and clinicians and have access to state-of-the-art whole body MRI, MRI-PET, low-dose CT scanners, advanced graphics workstations and parallel processing/GPU clusters.
For additional information, please visit: https://www.cc.nih.gov/meet-our-doctors/rsummers.html.
Qualifications:
Ph.D. in Computer Science, Electrical Engineering, or related discipline with experience in Computer Vision, Machine Learning, or Image Understanding domain, along with successful demonstration of key responsibilities.
Strong theoretical and practical background in computer vision, image and video analysis, such as object detection and recognition, statistical pattern recognition, machine learning, sparse methods and applied optimization. Prior knowledge about medical imaging is a plus but not a must. Enthusiasm in solving real world clinical imaging problems using large datasets, and hands-on coding skills and ability in C++ and Matlab.
This appointment is for one year and is renewable thereafter on a periodic basis (up to five years).
To Apply:
Applications should include a CV, brief statement of research interests and three letters of reference. Email application materials to Dr. Ronald Summers at rms@nih.gov.
DHHS and NIH are Equal Opportunity Employers.
Regards,
Sheeraz Akram
https://www.linkedin.com/in/sheerazakram/
More info
✔️ @ApplyTime
Neuroscience PhD Program, Tuebingen: deadline 15th Dec
The Max Planck Institute for Biological Cybernetics and the University
of Tübingen invite students from all over the world to apply for their
interdisciplinary 5-year PhD program leading to a PhD in
Neuroscience. Full funding will be available for top-ranked applicants.
We are seeking talented, curious and open-minded young scientists with
strong backgrounds in neuroscience, biomedical sciences, computational
science, applied mathematics, statistics, artificial intelligence, or
engineering. Successful candidates will possess a burning aspiration to
shape the future of neuroscience and the ability to thrive in a
fast-paced, interdisciplinary, environment.
The application deadline is December 15, 2019. Please visit:
https://www.kyb.tuebingen.mpg.de/phd-program
for more details and information about applying.
The PhD program is a collaboration between the Max Planck Institute for
Biological Cybernetics and the University of Tübingen. It is closely
affiliated with the renowned Graduate Training Centre of Neuroscience,
the centerpiece of neuroscience training in Tübingen. Students (who
should have been awarded a Bachelor's degree by September 2020) will
receive a broad interdisciplinary training in neuroscience, including
expert teaching by international renowned scientists and individual and
intensive mentoring.
Potential research topics cover a variety of fields in systems
neuroscience, cognitive and behavioral neuroscience, computational
neuroscience, translational and clinical neuroscience as well as
cellular and molecular neuroscience.
Teaching and research are conducted in English.
✔️ @ApplyTime
The Max Planck Institute for Biological Cybernetics and the University
of Tübingen invite students from all over the world to apply for their
interdisciplinary 5-year PhD program leading to a PhD in
Neuroscience. Full funding will be available for top-ranked applicants.
We are seeking talented, curious and open-minded young scientists with
strong backgrounds in neuroscience, biomedical sciences, computational
science, applied mathematics, statistics, artificial intelligence, or
engineering. Successful candidates will possess a burning aspiration to
shape the future of neuroscience and the ability to thrive in a
fast-paced, interdisciplinary, environment.
The application deadline is December 15, 2019. Please visit:
https://www.kyb.tuebingen.mpg.de/phd-program
for more details and information about applying.
The PhD program is a collaboration between the Max Planck Institute for
Biological Cybernetics and the University of Tübingen. It is closely
affiliated with the renowned Graduate Training Centre of Neuroscience,
the centerpiece of neuroscience training in Tübingen. Students (who
should have been awarded a Bachelor's degree by September 2020) will
receive a broad interdisciplinary training in neuroscience, including
expert teaching by international renowned scientists and individual and
intensive mentoring.
Potential research topics cover a variety of fields in systems
neuroscience, cognitive and behavioral neuroscience, computational
neuroscience, translational and clinical neuroscience as well as
cellular and molecular neuroscience.
Teaching and research are conducted in English.
✔️ @ApplyTime
Fully funded PhD Studentships in Games and Game AI (EPSRC, UK)
The IGGI Programme
The EPSRC Centre for Doctoral Training in Intelligent Games and Game Intelligence (IGGI) is the world's largest PhD research programme aimed at games.
IGGI has up to 12 studentships available for 2020/21 entry (starting September 2020) at the University of York or Queen Mary, University of London (QMUL). Studentships fund full fees (at a Home/EU rate) plus a tax-free living stipend, for a 4-year PhD programme.
The deadline for submitting applications for funded studentships is 23:59 GMT on 31st January 2020.
We also welcome self-funded applications throughout the year. All accepted IGGI students start at the beginning of the academic year in September.
See here for how to apply: http://www.iggi.org.uk/apply/
✔️ @ApplyTime
The IGGI Programme
The EPSRC Centre for Doctoral Training in Intelligent Games and Game Intelligence (IGGI) is the world's largest PhD research programme aimed at games.
IGGI has up to 12 studentships available for 2020/21 entry (starting September 2020) at the University of York or Queen Mary, University of London (QMUL). Studentships fund full fees (at a Home/EU rate) plus a tax-free living stipend, for a 4-year PhD programme.
The deadline for submitting applications for funded studentships is 23:59 GMT on 31st January 2020.
We also welcome self-funded applications throughout the year. All accepted IGGI students start at the beginning of the academic year in September.
See here for how to apply: http://www.iggi.org.uk/apply/
✔️ @ApplyTime
2.5 year postdoc at Lancaster University
We invite applications for a Senior Post-Doctoral Research Associate position to join the Next Generation Converged Digital infrastructure (NG-CDI) programme <http://www.ng-cdi.org> in the Department of Mathematics and Statistics at Lancaster University. NG-CDI is a £5m cross-disciplinary research project, jointly funded by BT and EPSRC, that will forge the foundational research needed to underpin the next generation converged digital infrastructure for the UK. The consortium brings together research groups from the Universities of Lancaster, Cambridge, Bristol and Surrey to work alongside BT, one of the world’s leading communications service providers.
The successful candidate on this 2.5 year post-doctoral position will work with David Leslie, developing recommender systems methodologies to suggest responses to anomalies detected on communications networks. You should have, or be close to completing, a PhD in Statistics, Machine Learning, Operations Research or a related discipline, with experience in one of more of the following areas: computational statistics; recommender systems; sequential decision-making.
Candidates who are considering making an application should find further details at <https://hr-jobs.lancs.ac.uk/Vacancy.aspx?ref=A2896>.
--
David Leslie, Professor of Statistical Learning,
Department of Mathematics and Statistics, Fylde College
Lancaster University, Lancaster, LA1 4YF, United Kingdom
d.leslie@lancaster.ac.uk
http://www.lancaster.ac.uk/fas/maths/people/david-leslie
✔️ @ApplyTime
We invite applications for a Senior Post-Doctoral Research Associate position to join the Next Generation Converged Digital infrastructure (NG-CDI) programme <http://www.ng-cdi.org> in the Department of Mathematics and Statistics at Lancaster University. NG-CDI is a £5m cross-disciplinary research project, jointly funded by BT and EPSRC, that will forge the foundational research needed to underpin the next generation converged digital infrastructure for the UK. The consortium brings together research groups from the Universities of Lancaster, Cambridge, Bristol and Surrey to work alongside BT, one of the world’s leading communications service providers.
The successful candidate on this 2.5 year post-doctoral position will work with David Leslie, developing recommender systems methodologies to suggest responses to anomalies detected on communications networks. You should have, or be close to completing, a PhD in Statistics, Machine Learning, Operations Research or a related discipline, with experience in one of more of the following areas: computational statistics; recommender systems; sequential decision-making.
Candidates who are considering making an application should find further details at <https://hr-jobs.lancs.ac.uk/Vacancy.aspx?ref=A2896>.
--
David Leslie, Professor of Statistical Learning,
Department of Mathematics and Statistics, Fylde College
Lancaster University, Lancaster, LA1 4YF, United Kingdom
d.leslie@lancaster.ac.uk
http://www.lancaster.ac.uk/fas/maths/people/david-leslie
✔️ @ApplyTime
Research Assistant: Speech, Language, and Cognition using Intracranial Recordings at Duke University
The Cogan Lab (PI: Gregory Cogan) at Duke University is seeking a research assistant to start ASAP (late 2019/Early 2020).
Research in the lab focuses on understanding the neural computations that underlie speech, language, and cognition. We use a combination of invasive recordings in adult and pediatric epilepsy patients: stereo-electroencephalography - SEEG, and electrocorticography – ECoG, and non-invasive recordings in healthy participants: electroencephalography – EEG. We also collaborate closely with the Viventi Lab (viventi.pratt.duke.edu - Department of Biomedical Engineering) to develop high density/channel count micro-electroencephalography (µECoG - < 2 mm spacing, up to 1024 channels) to record from functional neurosurgery patients (e.g. epilepsy, movement disorders, tumor patients) to better understand the micro-scale of human cognition. See the lab website for more information:
http://www.coganlab.org
Responsibilities include subject recruitment, data collection (including interacting with patients), data management, data analysis, helping to write papers for publication, and general administrivia. Working on weekends will also sometimes be necessary (with overtime pay).
The ideal candidate will be enthusiastic about a career in science/medicine/engineering, self-motivated, independent, creative, and have interest in speech/language, and/or cognitive/systems neuroscience. They will also have great interpersonal skills and a strong willingness to learn.
Candidates must have an undergraduate degree in a related field (e.g. Neuroscience, Psychology, Engineering, Biology, etc.), and experience with programming in Matlab and/or Python.
Duke University is an excellent and highly interdisciplinary place for research. Collaborators span multiple departments/institutes including the Duke Institute for Brain Sciences, the Center for Cognitive Neuroscience, Psychology and Neuroscience, Neurology, and Biomedical Engineering.
The position is open until filled. Interested applicants can send a CV, a brief statement of interest, as well as contact information for two references to: gregory [dot] cogan [at] duke [dot] edu
✔️ @ApplyTime
The Cogan Lab (PI: Gregory Cogan) at Duke University is seeking a research assistant to start ASAP (late 2019/Early 2020).
Research in the lab focuses on understanding the neural computations that underlie speech, language, and cognition. We use a combination of invasive recordings in adult and pediatric epilepsy patients: stereo-electroencephalography - SEEG, and electrocorticography – ECoG, and non-invasive recordings in healthy participants: electroencephalography – EEG. We also collaborate closely with the Viventi Lab (viventi.pratt.duke.edu - Department of Biomedical Engineering) to develop high density/channel count micro-electroencephalography (µECoG - < 2 mm spacing, up to 1024 channels) to record from functional neurosurgery patients (e.g. epilepsy, movement disorders, tumor patients) to better understand the micro-scale of human cognition. See the lab website for more information:
http://www.coganlab.org
Responsibilities include subject recruitment, data collection (including interacting with patients), data management, data analysis, helping to write papers for publication, and general administrivia. Working on weekends will also sometimes be necessary (with overtime pay).
The ideal candidate will be enthusiastic about a career in science/medicine/engineering, self-motivated, independent, creative, and have interest in speech/language, and/or cognitive/systems neuroscience. They will also have great interpersonal skills and a strong willingness to learn.
Candidates must have an undergraduate degree in a related field (e.g. Neuroscience, Psychology, Engineering, Biology, etc.), and experience with programming in Matlab and/or Python.
Duke University is an excellent and highly interdisciplinary place for research. Collaborators span multiple departments/institutes including the Duke Institute for Brain Sciences, the Center for Cognitive Neuroscience, Psychology and Neuroscience, Neurology, and Biomedical Engineering.
The position is open until filled. Interested applicants can send a CV, a brief statement of interest, as well as contact information for two references to: gregory [dot] cogan [at] duke [dot] edu
✔️ @ApplyTime
Cogan Lab
The Cogan Lab at Duke University: Cognitive Neuroscience of Speech
The Cogan Lab at Duke University: Using invasive human electrophysiology to study speech, language, and cognition
Open Research Position (PhD / PostDoc) in Biomedical Data Integration, Information Extraction, and Variant Assessment
The research group for „Knowledge Management in Bioinformatics“ at Humboldt-Universität zu Berlin has an open 3-year research position.
The position is part of the DFG-funded research unit "Beyond the Exome", a collaboration between the Charite Berlin, the MDC Berlin, and Humboldt-Universität. The research unit investigates the role of non-coding variations for rare diseases. The position is paid according to TVL-E13 (roughly 2.200 Euro / month), at the earliest possible start date and will run for three years. Our prime interest is to find a highly motivated PhD student, but applications from PostDocs are also ligible.
Applicants are expected to pursue research in the fields of biomedical data integration, information integration, and variant assessment. We will build an integrated resource of information on non-coding variations and their relationships to diseases. An important source of information will be the scientific literature, for which we develop semi-automated methods for information extraction and normalization. The gathered information will be used to predict the clinical relevance of variations. The holder of this position will be able to chose its own focus within these topics (integration, extraction, prediction).
The position has no teaching duties attached. Therefore, speaking German is not a pre-requite.
More information can be found at https://www.informatik.hu-berlin.de/wbi/jobs/wimi_1912.html
Sincerely,
Ulf Leser
✔️ @ApplyTime
The research group for „Knowledge Management in Bioinformatics“ at Humboldt-Universität zu Berlin has an open 3-year research position.
The position is part of the DFG-funded research unit "Beyond the Exome", a collaboration between the Charite Berlin, the MDC Berlin, and Humboldt-Universität. The research unit investigates the role of non-coding variations for rare diseases. The position is paid according to TVL-E13 (roughly 2.200 Euro / month), at the earliest possible start date and will run for three years. Our prime interest is to find a highly motivated PhD student, but applications from PostDocs are also ligible.
Applicants are expected to pursue research in the fields of biomedical data integration, information integration, and variant assessment. We will build an integrated resource of information on non-coding variations and their relationships to diseases. An important source of information will be the scientific literature, for which we develop semi-automated methods for information extraction and normalization. The gathered information will be used to predict the clinical relevance of variations. The holder of this position will be able to chose its own focus within these topics (integration, extraction, prediction).
The position has no teaching duties attached. Therefore, speaking German is not a pre-requite.
More information can be found at https://www.informatik.hu-berlin.de/wbi/jobs/wimi_1912.html
Sincerely,
Ulf Leser
✔️ @ApplyTime
Fully funded PhD candidate positions in Organismal Biology
IMPRS for Organismal Biology Radolfzell am Bodensee
Job denoscription
The International Max Planck Research School for Organismal Biology (IMPRS), a joint cooperation between the Max Planck Institute for Ornithology in Seewiesen, the newly founded Max Planck Institute of Animal Behavior with two research sites in Radolfzell and Konstanz, and the Department of Biology at the University of Konstanz, are seeking doctoral candidates (f/m/d). For 2020, the IMPRS announces various fully-funded doctoral projects (3 years) focusing on collective behavior, ecology, neuroethology, social structure, using quantitative analysis and virtual reality to name but a few of the exciting techniques used to answer research questions in the field of Organismal Biology (see https://www.orn.mpg.de/projects)!
Activities and responsibilities
The aim of the IMPRS is to provide first-class training and education for outstanding doctoral students from all over the world in a stimulating research environment. More than 40 scientists work on a variety of topics from animal migration, collective behavior, computational ecology, evolutionary genetics, neurobiology, sensory systems, social interactions and other related fields. Research includes lab and field work using different model organisms from plants, insects, fish, birds and mammals, as well as diverse techniques from animal tracking, large scale data analysis, molecular genetic analyses, optical imaging or social network analysis.
Qualification profile
We invite applications from all countries and from a wide range of backgrounds (biology, engineering science, physics, computer science). Applicants must have graduated with a Master's degree and/or an equivalent degree, in exceptional cases candidates with a 4-year study program BSc with honors (with a comprehensive scientific thesis work), shall be considered. It is not necessary to hold the final degree(s) at the time of the application. However, you must have been awarded your degree prior to the start of the program.
The standard of the degrees (i.e. eligibility) will be checked by University of Konstanz on a case-by-case basis.
Candidates need to be fluent in written and spoken English and - unless native speakers - have to document their proficiency in English (e.g. TOEFL).
We offer
All doctoral projects are fully funded for at least 3 years. On top of their own research, the IMPRS fellows attend laboratory courses and workshops in relevant transferable skills such as scientific writing and project management. Talks by invited speakers during our annual IMPRS symposium, student retreats, and conference participation complete the individually tailored curriculum.
Send application to
You can only apply via the three-tier electronical application process on the Institutes webpage. Please do not send any other type of application by regular mail or email as they will be rejected. The application must be completed in English only. Besides the online application form, we need several documents from you. Documents that are not in English or German need to be translated. You need to upload all the required documents as a single PDF-file.
The Max Planck Society and the University of Konstanz are equal opportunity employers and are committed to increasing the number of individuals with disabilities in their workforce and therefore we encourage applications from such qualified individuals. Furthermore, we seek to increase the number of women in those areas where they are underrepresented and therefore explicitly encourages women to apply.
Application deadline is January 15, 2020. Please only apply via http://www.orn.mpg.de/2383/Application.
✔️ @ApplyTime
IMPRS for Organismal Biology Radolfzell am Bodensee
Job denoscription
The International Max Planck Research School for Organismal Biology (IMPRS), a joint cooperation between the Max Planck Institute for Ornithology in Seewiesen, the newly founded Max Planck Institute of Animal Behavior with two research sites in Radolfzell and Konstanz, and the Department of Biology at the University of Konstanz, are seeking doctoral candidates (f/m/d). For 2020, the IMPRS announces various fully-funded doctoral projects (3 years) focusing on collective behavior, ecology, neuroethology, social structure, using quantitative analysis and virtual reality to name but a few of the exciting techniques used to answer research questions in the field of Organismal Biology (see https://www.orn.mpg.de/projects)!
Activities and responsibilities
The aim of the IMPRS is to provide first-class training and education for outstanding doctoral students from all over the world in a stimulating research environment. More than 40 scientists work on a variety of topics from animal migration, collective behavior, computational ecology, evolutionary genetics, neurobiology, sensory systems, social interactions and other related fields. Research includes lab and field work using different model organisms from plants, insects, fish, birds and mammals, as well as diverse techniques from animal tracking, large scale data analysis, molecular genetic analyses, optical imaging or social network analysis.
Qualification profile
We invite applications from all countries and from a wide range of backgrounds (biology, engineering science, physics, computer science). Applicants must have graduated with a Master's degree and/or an equivalent degree, in exceptional cases candidates with a 4-year study program BSc with honors (with a comprehensive scientific thesis work), shall be considered. It is not necessary to hold the final degree(s) at the time of the application. However, you must have been awarded your degree prior to the start of the program.
The standard of the degrees (i.e. eligibility) will be checked by University of Konstanz on a case-by-case basis.
Candidates need to be fluent in written and spoken English and - unless native speakers - have to document their proficiency in English (e.g. TOEFL).
We offer
All doctoral projects are fully funded for at least 3 years. On top of their own research, the IMPRS fellows attend laboratory courses and workshops in relevant transferable skills such as scientific writing and project management. Talks by invited speakers during our annual IMPRS symposium, student retreats, and conference participation complete the individually tailored curriculum.
Send application to
You can only apply via the three-tier electronical application process on the Institutes webpage. Please do not send any other type of application by regular mail or email as they will be rejected. The application must be completed in English only. Besides the online application form, we need several documents from you. Documents that are not in English or German need to be translated. You need to upload all the required documents as a single PDF-file.
The Max Planck Society and the University of Konstanz are equal opportunity employers and are committed to increasing the number of individuals with disabilities in their workforce and therefore we encourage applications from such qualified individuals. Furthermore, we seek to increase the number of women in those areas where they are underrepresented and therefore explicitly encourages women to apply.
Application deadline is January 15, 2020. Please only apply via http://www.orn.mpg.de/2383/Application.
✔️ @ApplyTime
PhD and Postdoc Positions in Machine Learning and Image Analysis at Oregon Health and Science University
Machine learning and deep learning are changing how biomedical research is conducted and how patients are diagnosed and treated. Computational image analysis leverages large-scale machine learning on high performance computing infrastructure to transform qualitative science to quantitative science. We develop innovative machine learning and computer vision algorithms and apply them to biomedicine so that they are used by biomedical researchers and physicians in the clinic. First and foremost, you will be trained to become a machine learning scientist (most of our graduates work in high-tech companies such as Microsoft, Nvidia, Intel, Apple, and Amazon). Furthermore, you will work in an exciting interdisciplinary environment with the potential to directly impact medical research, cancer care and patients’ lives.
You Will:
Work and collaborate with a diverse team of machine learning experts, imaging scientists, cancer biologists, radiologists and medical doctors to build a new generation of artificial intelligence in cancer research, detection and treatment.
Create algorithms and software in machine learning and deep learning for quantitative image analysis that enable discoveries in biomedicine and the evaluation of biological variation in diseases such as cancer. The tasks may include image registration, segmentation, characterization, quantification, and analysis. The imaging modalities may include electron microscopy, cyclic immunofluorescence, MRI and CT.
Leverage the unique opportunity within the field of computer vision and cancer research provided by the massive amount of image data at OHSU for conventional and unconventional modeling with clinical and biomedical relevance, such as (semi-)supervised, weakly supervised and unsupervised machine learning methods.
Have the opportunity to leverage modern computing clusters with hundreds of GPU’s and large cluster of DGX nodes.
Required Skills:
Bachelor’s or Master’s Degree in Computer Science, Electrical Engineering, Biomedical Engineering, Math, Physics, or other engineering and science field.
Strong analytical and computing skills.
Proficiency in advanced programming languages such as Python, Matlab, C/C++ or Java.
Interest in machine learning & deep learning and their application in medicine.
Knowledge about cancer biology and microscopic imaging is a plus.
OSHU is located in Portland, Oregon, in the Pacific Northwest. It is in close proximity of the “Silicon Forest” that consists of many high-tech companies. Portland boasts a thriving biotech scene with many biomedical companies, and is known for its mild climate, natural beauty, access to outdoors, and quality of living. Please send your CV to songx@oshu.edu.
✔️ @ApplyTime
Machine learning and deep learning are changing how biomedical research is conducted and how patients are diagnosed and treated. Computational image analysis leverages large-scale machine learning on high performance computing infrastructure to transform qualitative science to quantitative science. We develop innovative machine learning and computer vision algorithms and apply them to biomedicine so that they are used by biomedical researchers and physicians in the clinic. First and foremost, you will be trained to become a machine learning scientist (most of our graduates work in high-tech companies such as Microsoft, Nvidia, Intel, Apple, and Amazon). Furthermore, you will work in an exciting interdisciplinary environment with the potential to directly impact medical research, cancer care and patients’ lives.
You Will:
Work and collaborate with a diverse team of machine learning experts, imaging scientists, cancer biologists, radiologists and medical doctors to build a new generation of artificial intelligence in cancer research, detection and treatment.
Create algorithms and software in machine learning and deep learning for quantitative image analysis that enable discoveries in biomedicine and the evaluation of biological variation in diseases such as cancer. The tasks may include image registration, segmentation, characterization, quantification, and analysis. The imaging modalities may include electron microscopy, cyclic immunofluorescence, MRI and CT.
Leverage the unique opportunity within the field of computer vision and cancer research provided by the massive amount of image data at OHSU for conventional and unconventional modeling with clinical and biomedical relevance, such as (semi-)supervised, weakly supervised and unsupervised machine learning methods.
Have the opportunity to leverage modern computing clusters with hundreds of GPU’s and large cluster of DGX nodes.
Required Skills:
Bachelor’s or Master’s Degree in Computer Science, Electrical Engineering, Biomedical Engineering, Math, Physics, or other engineering and science field.
Strong analytical and computing skills.
Proficiency in advanced programming languages such as Python, Matlab, C/C++ or Java.
Interest in machine learning & deep learning and their application in medicine.
Knowledge about cancer biology and microscopic imaging is a plus.
OSHU is located in Portland, Oregon, in the Pacific Northwest. It is in close proximity of the “Silicon Forest” that consists of many high-tech companies. Portland boasts a thriving biotech scene with many biomedical companies, and is known for its mild climate, natural beauty, access to outdoors, and quality of living. Please send your CV to songx@oshu.edu.
✔️ @ApplyTime
PhD in modelling of heterogeneous medical data for clinical impact
The chronic lymphocytic leukemia (CLL) lab at Rigshospitalet, invite applications for an appointment as PhD student (health sciences, Copenhagen University) in modelling of heterogeneous medical data for clinical impact. The position is available from January, 2020 or according to mutual agreement.
Responsibilities and tasks
Machine learning on medical data has several challenges that need to be overcome for clinical implementation. This includes making predictions with low sample sizes, high dimensions and missing data. In this PhD you will be at the forefront of defining methodologies for handling missing data, combining multiple data-sources and providing trustable predictions for the clinic. You will carry out collaborative work with high profile partners at Technical University of Denmark (DTU), Institute Pasteur and PERSIMUNE.org for addressing key research questions related to chronic lymphocytic leukemia (CLL) and other lymphoproliferative malignancies. The research will focus on providing clinical value using ML strategies and includes:
Novel machine learning strategies for combining multidimensional clinical data from various sources such as flow cytometry, next generation DNA sequencing, gene expression & functional assays, baseline clinical, and para-clinical data.
Novel machine learning methods for cleaning and organizing clinical data with least bias.
Effective handling of missing data and low sample sizes.
Methods for interpretation of trained machine learning models with clinical viability in mind.
Publishing on High-Impact factor journals (NEJM, Blood, Nature Comm.)
Effective communication with medical doctors on modelling strategy choices and results.
Research environment
We offer a challenging PhD in an international environment. We value knowledge sharing and multi-disciplinarity. Hence, you are expected to cooperate and be eager to build relations with colleagues within the department and with collaboration partners. Through our collaboration with PERSIMUNE, you will be uniquely positioned to access rich and carefully curated datasets that are unattainable anywhere else in the world. Additionally, through our collaboration with DTU, you will have access to the high-performance computing (HPC) clusters for computational requirements. Our research group has the setup needed for fast testing in clinical trials through international collaborations (PreVent-ACaLL trial, clinicaltrials.gov: NCT03868722), therefore there is ample opportunity for your work as a modeller to have direct clinical impact. Our current research-group includes 5 scientific researchers (4 PhDs and 1 Post-Doc), 3 laboratory technicians, 20 clinical trial unit employees at the Department of Hematology, and 50+ data cleaning and structural IT technicians at the PERSIMUNE data lake. We strive for academic excellence, collegial respect and freedom tempered by responsibility. We also believe in each individual’s patterns of productivity. We welcome flexible time and location of working hours, as long as the quota for the full-time work week is reached.
More info
✔️ @ApplyTime
The chronic lymphocytic leukemia (CLL) lab at Rigshospitalet, invite applications for an appointment as PhD student (health sciences, Copenhagen University) in modelling of heterogeneous medical data for clinical impact. The position is available from January, 2020 or according to mutual agreement.
Responsibilities and tasks
Machine learning on medical data has several challenges that need to be overcome for clinical implementation. This includes making predictions with low sample sizes, high dimensions and missing data. In this PhD you will be at the forefront of defining methodologies for handling missing data, combining multiple data-sources and providing trustable predictions for the clinic. You will carry out collaborative work with high profile partners at Technical University of Denmark (DTU), Institute Pasteur and PERSIMUNE.org for addressing key research questions related to chronic lymphocytic leukemia (CLL) and other lymphoproliferative malignancies. The research will focus on providing clinical value using ML strategies and includes:
Novel machine learning strategies for combining multidimensional clinical data from various sources such as flow cytometry, next generation DNA sequencing, gene expression & functional assays, baseline clinical, and para-clinical data.
Novel machine learning methods for cleaning and organizing clinical data with least bias.
Effective handling of missing data and low sample sizes.
Methods for interpretation of trained machine learning models with clinical viability in mind.
Publishing on High-Impact factor journals (NEJM, Blood, Nature Comm.)
Effective communication with medical doctors on modelling strategy choices and results.
Research environment
We offer a challenging PhD in an international environment. We value knowledge sharing and multi-disciplinarity. Hence, you are expected to cooperate and be eager to build relations with colleagues within the department and with collaboration partners. Through our collaboration with PERSIMUNE, you will be uniquely positioned to access rich and carefully curated datasets that are unattainable anywhere else in the world. Additionally, through our collaboration with DTU, you will have access to the high-performance computing (HPC) clusters for computational requirements. Our research group has the setup needed for fast testing in clinical trials through international collaborations (PreVent-ACaLL trial, clinicaltrials.gov: NCT03868722), therefore there is ample opportunity for your work as a modeller to have direct clinical impact. Our current research-group includes 5 scientific researchers (4 PhDs and 1 Post-Doc), 3 laboratory technicians, 20 clinical trial unit employees at the Department of Hematology, and 50+ data cleaning and structural IT technicians at the PERSIMUNE data lake. We strive for academic excellence, collegial respect and freedom tempered by responsibility. We also believe in each individual’s patterns of productivity. We welcome flexible time and location of working hours, as long as the quota for the full-time work week is reached.
More info
✔️ @ApplyTime