Doctoral Researcher (f/m/d) Project C5 “Optimal design of chiral structures”
- part time (75%) -
Job denoscription
The Collaborative Research Center “Wave phenomena – analysis and numerics” (CRC 1173) has been funded by the German Research Foundation (DFG) since 2015. Its goal is to analytically understand, numerically simulate, and eventually manipulate wave propagation under realistic scenarios by intertwining analysis and numerics.
The context of the work in Project C5 is the interaction between the electromagnetic field and chiral matter, like chiral molecules, or artificial chiral nanostructures. One of the main objectives in the project is to further the current understanding of electromagnetic chirality measures related to the question: How chiral is an object? In this context, a general object will be represented by its scattering operator (far-field operator). It is foreseen that the transformation properties of the scattering operator under physically relevant groups will be one of the main subjects of study. Improving the ways that material chirality is quantified can have an impact both in practical problems like sensing of chiral molecules, and in solving theoretical puzzles like the decades-old chiral zeros problem. Also, aspects related to the actual design of electromagnetically chiral objects are important in this research. The work is done collaboratively with researchers from the Departments of Physics and Mathematics at the Karlsruhe Institute of Technology.
More info
✔️ @ApplyTime
- part time (75%) -
Job denoscription
The Collaborative Research Center “Wave phenomena – analysis and numerics” (CRC 1173) has been funded by the German Research Foundation (DFG) since 2015. Its goal is to analytically understand, numerically simulate, and eventually manipulate wave propagation under realistic scenarios by intertwining analysis and numerics.
The context of the work in Project C5 is the interaction between the electromagnetic field and chiral matter, like chiral molecules, or artificial chiral nanostructures. One of the main objectives in the project is to further the current understanding of electromagnetic chirality measures related to the question: How chiral is an object? In this context, a general object will be represented by its scattering operator (far-field operator). It is foreseen that the transformation properties of the scattering operator under physically relevant groups will be one of the main subjects of study. Improving the ways that material chirality is quantified can have an impact both in practical problems like sensing of chiral molecules, and in solving theoretical puzzles like the decades-old chiral zeros problem. Also, aspects related to the actual design of electromagnetically chiral objects are important in this research. The work is done collaboratively with researchers from the Departments of Physics and Mathematics at the Karlsruhe Institute of Technology.
More info
✔️ @ApplyTime
PhD-Position - Conception, Design and Development of an Electricity and Gas Grid Simulation Environment for System Analysis using an HPC Infrastructure
Your Job:
Analysis of the current state of the art in quasi dynamic and dynamic simulation of power and gas grids
Development and programming of a simulation environment that is able to capture the interaction between different energy grids faster than real-time using HPC infrastructures
Development of integrated software tools for automated data analysis, which facilitate sorting and structuring for the user and provide a supportive approach for research by means of integrated administration, interpretation and evaluation mechanisms
Development and implementation of a data basis and models for the energy infrastructures on the campus Forschungszentrum Jülich
Validation of the implemented simulation models
More info
✔️ @ApplyTime
Your Job:
Analysis of the current state of the art in quasi dynamic and dynamic simulation of power and gas grids
Development and programming of a simulation environment that is able to capture the interaction between different energy grids faster than real-time using HPC infrastructures
Development of integrated software tools for automated data analysis, which facilitate sorting and structuring for the user and provide a supportive approach for research by means of integrated administration, interpretation and evaluation mechanisms
Development and implementation of a data basis and models for the energy infrastructures on the campus Forschungszentrum Jülich
Validation of the implemented simulation models
More info
✔️ @ApplyTime
www.fz-juelich.de
Forschungszentrum Jülich - Current Vacancies - PhD-Position - Conception, Design and Development of an Electricity and Gas Grid…
PhD Fellowship in Functional Proteomics and Tissue Plasticity
The DNRF Centre of Excellence, Center for Functional Genomics and Tissue Plasticity (ATLAS) at the University of Southern Denmark invites applications for a PhD scholarship from outstanding candidates with a keen interest in applying mass spectrometry-based functional proteomics to understand the molecular and cellular basis underlying tissue plasticity. The position is available from 1 February 2019, or as soon as possible thereafter. Application deadline: 9 December 2019.
More info
✔️ @ApplyTime
The DNRF Centre of Excellence, Center for Functional Genomics and Tissue Plasticity (ATLAS) at the University of Southern Denmark invites applications for a PhD scholarship from outstanding candidates with a keen interest in applying mass spectrometry-based functional proteomics to understand the molecular and cellular basis underlying tissue plasticity. The position is available from 1 February 2019, or as soon as possible thereafter. Application deadline: 9 December 2019.
More info
✔️ @ApplyTime
SDU
PhD Fellowship in Functional Proteomics and Tissue Plasticity - University of Southern Denmark, SDU
The DNRF Centre of Excellence, <a href="https://www.sdu.dk/en/ATLAS" target="_blank" rel="noopener">Center for Functional Genomics and Tissue Plasticity (ATLAS) at the University of Southern Denmark invites applications for a PhD scholarship from outstanding…
PhD scholarship at the Department of Business and Economics
The successful applicant must be able to demonstrate
Excellent grades at the bachelor and master's levels in economics, political science, public health or related social scientific disciplines;
Profound knowledge of statistical methods;
Good knowledge of Stata or similar statistical programs;
Excellent communication skills in English (enclosing results of TOEFL and GRE tests is encouraged but not mandatory).
For further information, please contact Prof. Jørgen T. Lauridsen (jtl@sam.sdu.dk) for queries in general or matters related to Economics, Public Health or Social Science. For matters related to Political Science, you may contact Pieter Vanhuysse (vanhuysse@sam.sdu.dk).
More info
✔️ @ApplyTime
The successful applicant must be able to demonstrate
Excellent grades at the bachelor and master's levels in economics, political science, public health or related social scientific disciplines;
Profound knowledge of statistical methods;
Good knowledge of Stata or similar statistical programs;
Excellent communication skills in English (enclosing results of TOEFL and GRE tests is encouraged but not mandatory).
For further information, please contact Prof. Jørgen T. Lauridsen (jtl@sam.sdu.dk) for queries in general or matters related to Economics, Public Health or Social Science. For matters related to Political Science, you may contact Pieter Vanhuysse (vanhuysse@sam.sdu.dk).
More info
✔️ @ApplyTime
Neural Computation lab
We welcome inquiries about joining the lab. Our group is highly multidisciplinary, and is home to students and postdocs from diverse fields, ranging from physical and engineering sciences, to molecular and cell biology, as well as those with a background in mathematics or statistics. For all inquiries, please email Michael Häusser (m.hausser@ucl.ac.uk).
Postdoctoral positions
We aim to attract ambitious, hardworking postdocs interested in attacking major challenges in neuroscience. There are a range of funding opportunities available.
NEW: we currently have a postdoctoral position available for a project involving the use of the revolutionary new Neuropixels probes as part of the International Brain Laboratory. For more information, contact Michael Häusser (m.hausser@ucl.ac.uk).
PhD positions
Most PhD students join the lab by enrolling in one of UCL's outstanding 4-year PhD programmes, such as the 4-year PhD Programme in Neuroscience; the CoMPLEX PhD programme, the Gatsby Unit PhD Programme, or the MRC Doctoral Training Account. If you are not eligible for these programmes, or would like to make an informal inquiry prior to making an application, please get in touch.
Internships
We welcome applications from UCL students interested in doing a final-year project in the lab. We also welcome candidates for lab internships throughout the year; those interested in doing a summer project in the lab should contact us well in advance of the deadlines for summer studentship applications from the Wellcome Trust and the Physiological Society.
More info
✔️ @ApplyTime
We welcome inquiries about joining the lab. Our group is highly multidisciplinary, and is home to students and postdocs from diverse fields, ranging from physical and engineering sciences, to molecular and cell biology, as well as those with a background in mathematics or statistics. For all inquiries, please email Michael Häusser (m.hausser@ucl.ac.uk).
Postdoctoral positions
We aim to attract ambitious, hardworking postdocs interested in attacking major challenges in neuroscience. There are a range of funding opportunities available.
NEW: we currently have a postdoctoral position available for a project involving the use of the revolutionary new Neuropixels probes as part of the International Brain Laboratory. For more information, contact Michael Häusser (m.hausser@ucl.ac.uk).
PhD positions
Most PhD students join the lab by enrolling in one of UCL's outstanding 4-year PhD programmes, such as the 4-year PhD Programme in Neuroscience; the CoMPLEX PhD programme, the Gatsby Unit PhD Programme, or the MRC Doctoral Training Account. If you are not eligible for these programmes, or would like to make an informal inquiry prior to making an application, please get in touch.
Internships
We welcome applications from UCL students interested in doing a final-year project in the lab. We also welcome candidates for lab internships throughout the year; those interested in doing a summer project in the lab should contact us well in advance of the deadlines for summer studentship applications from the Wellcome Trust and the Physiological Society.
More info
✔️ @ApplyTime
PhD Studentship in Orthopaedic Implant Technology, - Ref:1834900
A 3-year PhD studentship is available at the Royal National Orthopaedic Hospital NHS Trust (RNOH), which is the largest orthopaedic hospital in the UK and considered world leader in musculoskeletal science.
Studentship Denoscription
Career Opportunities
You will complete this PhD with: (1) a track-record of peer-reviewed publications), (2) an expertise in implant, imaging and computational analysis methods and (3) an ability to interact with engineers and surgeons of all levels. This will offer you a strong foundation for building an academic career but equally, your experience will position you very well for a successful career in industry, where clinical knowledge in engineers is sought after (we have worked with all major orthopaedic manufacturers).
Background
The Magnetic Expansion Control (MAGEC) rod is used for the treatment of early onset scoliosis. Early clinical results are promising with fewer complications than patients with traditional growth rods. However, one third have still reported complications with many of these requiring an unplanned early implant revision. Our centre is leading research aimed at improving the performance of orthopaedic implants by working closely with surgeons and engineers. Retrieval analysis of removed implants can help understanding of their failure mechanisms and identify common surgeon, implant or patient risk factors for early failure.
More info
✔️ @ApplyTime
A 3-year PhD studentship is available at the Royal National Orthopaedic Hospital NHS Trust (RNOH), which is the largest orthopaedic hospital in the UK and considered world leader in musculoskeletal science.
Studentship Denoscription
Career Opportunities
You will complete this PhD with: (1) a track-record of peer-reviewed publications), (2) an expertise in implant, imaging and computational analysis methods and (3) an ability to interact with engineers and surgeons of all levels. This will offer you a strong foundation for building an academic career but equally, your experience will position you very well for a successful career in industry, where clinical knowledge in engineers is sought after (we have worked with all major orthopaedic manufacturers).
Background
The Magnetic Expansion Control (MAGEC) rod is used for the treatment of early onset scoliosis. Early clinical results are promising with fewer complications than patients with traditional growth rods. However, one third have still reported complications with many of these requiring an unplanned early implant revision. Our centre is leading research aimed at improving the performance of orthopaedic implants by working closely with surgeons and engineers. Retrieval analysis of removed implants can help understanding of their failure mechanisms and identify common surgeon, implant or patient risk factors for early failure.
More info
✔️ @ApplyTime
A 3-year fully-funded PhD position is available through the Alzheimer's Society scheme in UK Dementia Research Institute at the University of Cambridge.
The project aims to identify the components of the intrinsic cellular machineries for handling aggregation-prone proteins, and characterise circumstances in which these machineries are activated, with the view to identifying new therapeutic targets to ameliorate/prevent the aggregation load in neuronal cells (associated with neurodegenerative diseases). The project stems from in-house developed technology enabling detection of failures in the protein-folding quality control system with high space-time resolution, and its ability to visualise the existence of the aggregation-resolving activity in live cells.
Student will develop the experimental models for monitoring protein quality control and aggregation in live iPSC-derived neurons, and analyse the activity of the intrinsic systems applying a range of biochemical, molecular biology and advanced light imaging techniques. Along with molecular biology/biochemistry, the work will involve training in light microscopy techniques such as Fluorescence Lifetime Imaging, super-resolution microscopy and single particle tracking using state of the art optics and software. This work will be conducted with support of interdisciplinary collaborators including physicists and computer scientists, enabling optical tools, mathematical modeling and data analysis.
More info
✔️ @ApplyTime
The project aims to identify the components of the intrinsic cellular machineries for handling aggregation-prone proteins, and characterise circumstances in which these machineries are activated, with the view to identifying new therapeutic targets to ameliorate/prevent the aggregation load in neuronal cells (associated with neurodegenerative diseases). The project stems from in-house developed technology enabling detection of failures in the protein-folding quality control system with high space-time resolution, and its ability to visualise the existence of the aggregation-resolving activity in live cells.
Student will develop the experimental models for monitoring protein quality control and aggregation in live iPSC-derived neurons, and analyse the activity of the intrinsic systems applying a range of biochemical, molecular biology and advanced light imaging techniques. Along with molecular biology/biochemistry, the work will involve training in light microscopy techniques such as Fluorescence Lifetime Imaging, super-resolution microscopy and single particle tracking using state of the art optics and software. This work will be conducted with support of interdisciplinary collaborators including physicists and computer scientists, enabling optical tools, mathematical modeling and data analysis.
More info
✔️ @ApplyTime
www.jobs.cam.ac.uk
PhD Studentship - Job Opportunities - University of Cambridge
PhD Studentship in the Department of Clinical Neurosciences at the University of Cambridge.
PhD candidate within Faculty of Sociology, Anthropology and Folklore, School of Social Sciences, University of Iceland
We are looking for applicants for a full-time position for a Ph.D. student in sociology at the Faculty of Sociology, Anthropology and Folklore. The funding is for three years, but each hiring period is one year according to requirements about the progress of the project.
Hide More information
Field of work
The project focuses on social inequality and requires analysis of quantitative data and writing peer-reviewed articles in English. The project is a part of an international study of inequality (International Social Survey Programme, ISSP), and consists of data from surveys collected from the public in about 40 countries that measure people´s attitudes and experiences in regard to inequality. In addition, there is a possibility of collecting and analyzing qualitative data with a specific focus on Iceland.
Qualification requirements
Applicants must have completed an M.A.-degree and to fulfill the requirement of entry to doctoral studies at the Faculty of Sociology, Anthropology, and Folklore, or to be current doctoral students at the Faculty
Good writing skills in English
Experience with quantitative methods
Experience with qualitative methods is a plus
Good interactional skills
Ability to be initiative and to work independently
More info
✔️ @ApplyTime
We are looking for applicants for a full-time position for a Ph.D. student in sociology at the Faculty of Sociology, Anthropology and Folklore. The funding is for three years, but each hiring period is one year according to requirements about the progress of the project.
Hide More information
Field of work
The project focuses on social inequality and requires analysis of quantitative data and writing peer-reviewed articles in English. The project is a part of an international study of inequality (International Social Survey Programme, ISSP), and consists of data from surveys collected from the public in about 40 countries that measure people´s attitudes and experiences in regard to inequality. In addition, there is a possibility of collecting and analyzing qualitative data with a specific focus on Iceland.
Qualification requirements
Applicants must have completed an M.A.-degree and to fulfill the requirement of entry to doctoral studies at the Faculty of Sociology, Anthropology, and Folklore, or to be current doctoral students at the Faculty
Good writing skills in English
Experience with quantitative methods
Experience with qualitative methods is a plus
Good interactional skills
Ability to be initiative and to work independently
More info
✔️ @ApplyTime
Doctoral Grant by the University Research Fund (BOF) in the area of Administrative Law
This doctoral research project aims to identify general principles of proof in Belgian administrative law. This is an aspect of general administrative law on which, despite its importance, a general theory based on fundamental research is lacking in Belgium. The project requires a thorough study of the case law of the Belgian administrative courts and involves comparative law too. The researcher will be embedded in the research group Government & Law (https://www.uantwerpen.be/en/research-groups/government-and-law/).
Job denoscription
You prepare a doctoral thesis on the basis of a project ennoscriptd ‘Towards a Theory on General Principles of Proof in Administrative Law’.
You publish scientific articles related to the research project of the assignment.
You contribute to teaching and research in the Faculty of Law, research group Government & Law.
More info
✔️ @ApplyTime
This doctoral research project aims to identify general principles of proof in Belgian administrative law. This is an aspect of general administrative law on which, despite its importance, a general theory based on fundamental research is lacking in Belgium. The project requires a thorough study of the case law of the Belgian administrative courts and involves comparative law too. The researcher will be embedded in the research group Government & Law (https://www.uantwerpen.be/en/research-groups/government-and-law/).
Job denoscription
You prepare a doctoral thesis on the basis of a project ennoscriptd ‘Towards a Theory on General Principles of Proof in Administrative Law’.
You publish scientific articles related to the research project of the assignment.
You contribute to teaching and research in the Faculty of Law, research group Government & Law.
More info
✔️ @ApplyTime
Doctoral Grant (BOF), Multimorbidity and its cost in the Belgium health system - 2019BAPDOCPROEX275
The Faculty of Medicine and Health Sciences is seeking to fill a full-time (100%) position for a
Doctoral Grant by the University Research Fund (BOF) in the area of Multimorbidity and its cost in the Belgium health system
Multimorbidity is a growing phenomenon, but research has only recently taken off. How patients with multimorbidity use health care is not well known, despite its implications on quality and cost. This PhD aims to improve understanding of the burden, management and cost of multimorbidity in the Belgium health system.
The Department of Primary and interdisciplinary care and the Department of Social Epidemiology and Health Policy lead this doctoral research project. It is part of the new spearhead research on quality of integrated care.
More info
✔️ @ApplyTime
The Faculty of Medicine and Health Sciences is seeking to fill a full-time (100%) position for a
Doctoral Grant by the University Research Fund (BOF) in the area of Multimorbidity and its cost in the Belgium health system
Multimorbidity is a growing phenomenon, but research has only recently taken off. How patients with multimorbidity use health care is not well known, despite its implications on quality and cost. This PhD aims to improve understanding of the burden, management and cost of multimorbidity in the Belgium health system.
The Department of Primary and interdisciplinary care and the Department of Social Epidemiology and Health Policy lead this doctoral research project. It is part of the new spearhead research on quality of integrated care.
More info
✔️ @ApplyTime
PhD Student positions in Engineering Psychology with focus on Clinical Research
Lulea
Ref 5010-2019
The research subject Engineering Psychology is looking for a PhD student within the newly established Research School in the field of Humans and Technology at Luleå University of Technology. As a doctoral student in the Research School, you will become part of the research environment in the Human and Technology division with over 60 employees. You will be placed in the Engineering Psychology subject group and you will also be a part of the Research School along with doctoral students in Human Work Science, Industrial Design, and Product Innovation. The Research School will commence during the 2019/2020 academic year.
Research in Engineering Psychology is concerned primarily with the interaction between humans and the natural and social environment. Psychology is an exciting subject that can be applied in most situations where people are involved, which means that the research areas studied all play an important role in society and the business community. We offer our doctoral students a dynamic, international research environment in close collaboration with industries and leading universities around the world.
More info
✔️ @ApplyTime
Lulea
Ref 5010-2019
The research subject Engineering Psychology is looking for a PhD student within the newly established Research School in the field of Humans and Technology at Luleå University of Technology. As a doctoral student in the Research School, you will become part of the research environment in the Human and Technology division with over 60 employees. You will be placed in the Engineering Psychology subject group and you will also be a part of the Research School along with doctoral students in Human Work Science, Industrial Design, and Product Innovation. The Research School will commence during the 2019/2020 academic year.
Research in Engineering Psychology is concerned primarily with the interaction between humans and the natural and social environment. Psychology is an exciting subject that can be applied in most situations where people are involved, which means that the research areas studied all play an important role in society and the business community. We offer our doctoral students a dynamic, international research environment in close collaboration with industries and leading universities around the world.
More info
✔️ @ApplyTime
PhD student position in Political Science
Lulea
Ref 5014-2019
We are looking for a PhD students in political Science within a new Research School at Luleå University of Technology’s Social Sciences Division. The Division includes around 50 employees in the areas of Political science, Economics, History and Jurisprudence. The student will be placed in the Political Science group and be part of a newly established Research School.
The Research School will start during the 2019/2020 academic year. Its overarching theme is how society can realize the global Sustainable Development Goals (UN 2030 Agenda for Sustainable Development), which will require new forms of collaboration, new business models, new technologies, changes in legislation, reassessed norms, and different societal policies and policy instruments. Changes like these will create winners and losers and produce important goal and value conflicts.
Research at the Social Sciences Division is oriented towards natural resources, environmental and energy issues and frequently takes place in a multidisciplinary environment where academic subjects from the Faculty of Science and Technology also participate. We strive for an international perspective in our education and research.
More info
✔️ @ApplyTime
Lulea
Ref 5014-2019
We are looking for a PhD students in political Science within a new Research School at Luleå University of Technology’s Social Sciences Division. The Division includes around 50 employees in the areas of Political science, Economics, History and Jurisprudence. The student will be placed in the Political Science group and be part of a newly established Research School.
The Research School will start during the 2019/2020 academic year. Its overarching theme is how society can realize the global Sustainable Development Goals (UN 2030 Agenda for Sustainable Development), which will require new forms of collaboration, new business models, new technologies, changes in legislation, reassessed norms, and different societal policies and policy instruments. Changes like these will create winners and losers and produce important goal and value conflicts.
Research at the Social Sciences Division is oriented towards natural resources, environmental and energy issues and frequently takes place in a multidisciplinary environment where academic subjects from the Faculty of Science and Technology also participate. We strive for an international perspective in our education and research.
More info
✔️ @ApplyTime
PhD student positions in Entrepreneurship and Innovation
Lulea
Ref 5019-2019
The research subject Entrepreneurship and Innovation is seeking a PhD student within the framework of a newly started research school in Industrial Engineering and Management at Luleå University of Technology. As a doctoral student in the research school, you become part of the research environment within the Industrial Engineering and Management department with about sixty employees. You are placed within the subject group for Entrepreneurship and Innovation and are part of the graduate school together with doctoral students in Accounting and control, Quality Technology and Logistics and Industrial Marketing. The graduate school will start during the fall 2019 and spring 2020.
Entrepreneurship and innovation at Luleå University of Technology was established in 2006 and today has about 20 employees with a broad competence base. Our goal is to be an international center for the development and dissemination of future ideas in entrepreneurship and innovation. Entrepreneurship and innovation include organizational development with a particular focus on business development based on innovative products, services and production solutions, as well as ways of managing and organizing businesses. The research group collaborates with large national and international companies, small and medium-sized enterprises (SMEs), policy makers and other research groups. Research results are produced in close collaboration with industry and other community actors. To strengthen our research in business model innovation, we are now seeking a PhD student.
More info
✔️ @ApplyTime
Lulea
Ref 5019-2019
The research subject Entrepreneurship and Innovation is seeking a PhD student within the framework of a newly started research school in Industrial Engineering and Management at Luleå University of Technology. As a doctoral student in the research school, you become part of the research environment within the Industrial Engineering and Management department with about sixty employees. You are placed within the subject group for Entrepreneurship and Innovation and are part of the graduate school together with doctoral students in Accounting and control, Quality Technology and Logistics and Industrial Marketing. The graduate school will start during the fall 2019 and spring 2020.
Entrepreneurship and innovation at Luleå University of Technology was established in 2006 and today has about 20 employees with a broad competence base. Our goal is to be an international center for the development and dissemination of future ideas in entrepreneurship and innovation. Entrepreneurship and innovation include organizational development with a particular focus on business development based on innovative products, services and production solutions, as well as ways of managing and organizing businesses. The research group collaborates with large national and international companies, small and medium-sized enterprises (SMEs), policy makers and other research groups. Research results are produced in close collaboration with industry and other community actors. To strengthen our research in business model innovation, we are now seeking a PhD student.
More info
✔️ @ApplyTime
2-year Research Grant in Augmented Reality for Art and Cultural Heritage
he Signals and Images Laboratory of ISTI-CNR (National Research Council of Italy) is looking for possible candidates for a two-year research grant (28,000 EURO per year). The official announcement is imminent.
The research topics will focus on Augmented Reality applied to art and cultural heritage.
Requirements: MSc in computer science (or computer engineering), age less than 36 years.
Required knowledge: mobile platforms development (Android, iOS), knowledge of Unity 3D.
For further information, please contact massimo.magrini@isti.cnr.it
Thank you and best regards,
Davide Moroni
--
Davide Moroni, PhD
Signals & Images LAB
Institute of Information Science and Technologies
✔️ @ApplyTime
he Signals and Images Laboratory of ISTI-CNR (National Research Council of Italy) is looking for possible candidates for a two-year research grant (28,000 EURO per year). The official announcement is imminent.
The research topics will focus on Augmented Reality applied to art and cultural heritage.
Requirements: MSc in computer science (or computer engineering), age less than 36 years.
Required knowledge: mobile platforms development (Android, iOS), knowledge of Unity 3D.
For further information, please contact massimo.magrini@isti.cnr.it
Thank you and best regards,
Davide Moroni
--
Davide Moroni, PhD
Signals & Images LAB
Institute of Information Science and Technologies
✔️ @ApplyTime
Seeking a Studentship Position in AI-ML-NLP-DataScience areas in Computer Science
Dear Researchers, Professors and colleagues,
Greetings! I trust you are doing great.
I am Partha Pratim Saha, a Senior Data Scientist, looking for an Integrated Master's cum PhD studentship position across the globe in the areas of Artificial Intelligence, Machine Learning, Data Science, Natural Language Processing or in related areas of Computer Science.
I would expect a scholarship as I am planning to start this position as soon as possible. Please let me know if you and/or any of your colleagues are interested in taking a student in the similar research group.
Thanking you. I look forward hearing from you soon.
With Sincerely,
Partha Pratim Saha
Email: technical.partha@gmail.com
✔️ @ApplyTime
Dear Researchers, Professors and colleagues,
Greetings! I trust you are doing great.
I am Partha Pratim Saha, a Senior Data Scientist, looking for an Integrated Master's cum PhD studentship position across the globe in the areas of Artificial Intelligence, Machine Learning, Data Science, Natural Language Processing or in related areas of Computer Science.
I would expect a scholarship as I am planning to start this position as soon as possible. Please let me know if you and/or any of your colleagues are interested in taking a student in the similar research group.
Thanking you. I look forward hearing from you soon.
With Sincerely,
Partha Pratim Saha
Email: technical.partha@gmail.com
✔️ @ApplyTime
Postdoctoral and PhD positions on Natural Language Processing / Information Extraction, INESC TEC / University of Porto.
-----------------------------------------------------------------------------------------------------------------------------------------------------
The Artificial Intelligence Lab (LIAAD) of INESC TEC / U. Porto is (https://www.inesctec.pt/en/centres/liaad) is looking for one highly motivated post doc and two MSc holders to join the team of researchers working on the Text2Story project. The topic is Narrative Extraction from Text. The aims of the project are to develop Machine Learning and Information Extraction algorithms and tools for Identifying, formally representing and reusing narrative structures from textual sources.
The selected candidates will join the Machine Learning and NLP team of LIAAD-INESC TEC (FCUP or INESC TEC) and will have the opportunity to work in an exciting and young environment in close interaction with research engineers, PhD students and post-doctoral researchers who are working on varied aspects that concern Machine Learning, Information Extraction and Computer Science.
The ideal candidates will have a PhD (or MSc) in NLP or equivalent and the following skills:
* Strong motivation to work with NLP from algorithms to demos and tools;
* Theoretical background and hands-on experience on NLP, Machine Learning, Information Retrieval and Information Extraction;
* Good communication skills and ability to cooperate within a team;
* Good knowledge of programming languages such as, Python, R and Java;
* Knowledge of Python and development tools (e.g. GIT);
* Being able to use Portuguese as a language of study is important.
For the postdoc mostly:
* Motivation to co-coordinate work-packages, co-supervise students and help with project management;
* Motivation to articulate with other projects on the topic and go after funding for the research line;
This positions are supported by the FCT project Text2Story. FCT is the Portuguese National Science Funding Agency.
For more information and applications:
Postdoc: https://www.inesctec.pt/en/opportunities/natural-language-processing-machine-learning-AE2019-0343
MSc: https://www.inesctec.pt/en/opportunities/machine-learning-AE2019-0342
✔️ @ApplyTime
-----------------------------------------------------------------------------------------------------------------------------------------------------
The Artificial Intelligence Lab (LIAAD) of INESC TEC / U. Porto is (https://www.inesctec.pt/en/centres/liaad) is looking for one highly motivated post doc and two MSc holders to join the team of researchers working on the Text2Story project. The topic is Narrative Extraction from Text. The aims of the project are to develop Machine Learning and Information Extraction algorithms and tools for Identifying, formally representing and reusing narrative structures from textual sources.
The selected candidates will join the Machine Learning and NLP team of LIAAD-INESC TEC (FCUP or INESC TEC) and will have the opportunity to work in an exciting and young environment in close interaction with research engineers, PhD students and post-doctoral researchers who are working on varied aspects that concern Machine Learning, Information Extraction and Computer Science.
The ideal candidates will have a PhD (or MSc) in NLP or equivalent and the following skills:
* Strong motivation to work with NLP from algorithms to demos and tools;
* Theoretical background and hands-on experience on NLP, Machine Learning, Information Retrieval and Information Extraction;
* Good communication skills and ability to cooperate within a team;
* Good knowledge of programming languages such as, Python, R and Java;
* Knowledge of Python and development tools (e.g. GIT);
* Being able to use Portuguese as a language of study is important.
For the postdoc mostly:
* Motivation to co-coordinate work-packages, co-supervise students and help with project management;
* Motivation to articulate with other projects on the topic and go after funding for the research line;
This positions are supported by the FCT project Text2Story. FCT is the Portuguese National Science Funding Agency.
For more information and applications:
Postdoc: https://www.inesctec.pt/en/opportunities/natural-language-processing-machine-learning-AE2019-0343
MSc: https://www.inesctec.pt/en/opportunities/machine-learning-AE2019-0342
✔️ @ApplyTime
INESC TEC
Artificial Intelligence and Decision Support - INESC TEC
INESC TEC research on Artificial Intelligence and Decision Support
University of York, PhD in Mechanistic Biology
Project noscript: The circadian clock in the ageing plant
https://www.findaphd.com/phds/project/the-circadian-clock-in-the-ageing-plant/?p112907
Project Denoscription
Plants respond to environmental signals in a time-of-day dependent manner,
but we do not yet know how this process is affected by age. In the long term,
we would like to predict how changes in weather throughout a growth season
will influence a plant, so farmers can plan their harvests even under
unpredictable weather patterns caused by climate change.
This PhD project will investigate how the genetic targets of the circadian clock
change as plants age, with a focus on environmental signalling and
developmental genes. We are looking for a candidate that wants to develop
into a well-rounded computational and experimental scientist. For instance, a
great candidate could be a statistics or computer science graduate who wants
some exposure to experimental work or a biology student who wishes to focus
their PhDs on bioinformatics and statistics.
From a ‘data science’ perspective, the project is interesting because it will
include ‘time series’ of ‘time series’ across different time scales
(developmental time series of circadian time series). From a biological
perspective, it focusses on a fundamental question: how is circadian
regulation of gene expression affected by ageing?
ML aspects of project: supervised and unsupervised learning on multi-scale longitudinal data sets
Funding Notes
This is a BBSRC White Rose DTP studentship fully funded for four years and covers: (i) a tax-free annual stipend at the standard Research Council rate (£15,009 estimated for 2020 entry), (ii) research costs, and (iii) tuition fees at the UK/EU rate.
References
Entry requirements: Students with, or expecting to gain, at least an upper second class honours degree, or equivalent, are invited to apply. The interdisciplinary nature of this research project means that we welcome applications from students with backgrounds in any biological, chemical, and/or physical science, or students with mathematical backgrounds who are interested in using their skills in addressing biological questions
✔️ @ApplyTime
Project noscript: The circadian clock in the ageing plant
https://www.findaphd.com/phds/project/the-circadian-clock-in-the-ageing-plant/?p112907
Project Denoscription
Plants respond to environmental signals in a time-of-day dependent manner,
but we do not yet know how this process is affected by age. In the long term,
we would like to predict how changes in weather throughout a growth season
will influence a plant, so farmers can plan their harvests even under
unpredictable weather patterns caused by climate change.
This PhD project will investigate how the genetic targets of the circadian clock
change as plants age, with a focus on environmental signalling and
developmental genes. We are looking for a candidate that wants to develop
into a well-rounded computational and experimental scientist. For instance, a
great candidate could be a statistics or computer science graduate who wants
some exposure to experimental work or a biology student who wishes to focus
their PhDs on bioinformatics and statistics.
From a ‘data science’ perspective, the project is interesting because it will
include ‘time series’ of ‘time series’ across different time scales
(developmental time series of circadian time series). From a biological
perspective, it focusses on a fundamental question: how is circadian
regulation of gene expression affected by ageing?
ML aspects of project: supervised and unsupervised learning on multi-scale longitudinal data sets
Funding Notes
This is a BBSRC White Rose DTP studentship fully funded for four years and covers: (i) a tax-free annual stipend at the standard Research Council rate (£15,009 estimated for 2020 entry), (ii) research costs, and (iii) tuition fees at the UK/EU rate.
References
Entry requirements: Students with, or expecting to gain, at least an upper second class honours degree, or equivalent, are invited to apply. The interdisciplinary nature of this research project means that we welcome applications from students with backgrounds in any biological, chemical, and/or physical science, or students with mathematical backgrounds who are interested in using their skills in addressing biological questions
✔️ @ApplyTime
www.FindAPhD.com
The circadian clock in the ageing plant at University of York on FindAPhD.com
PhD Project - The circadian clock in the ageing plant at University of York, listed on FindAPhD.com
Postdoc position in Adaptive Online Learning and Learning Theory
Dear all,
I have an opening for a postdoc position in my group to work with me on Adaptive Online Learning and other topics in Statistical Learning Theory.
The ideal starting date would be the fall of 2020 or early 2021.
A requirement is to have multiple theory papers at COLT/NeurIPS/ICML/JMLR or similar.
If you are interested and are attending NeurIPS next week, then please contact me to arrange to meet up informally at the conference.
To apply, send me your CV and a short denoscription of your background at tim@timvanerven.nl.
Best regards,
Tim
✔️ @ApplyTime
Dear all,
I have an opening for a postdoc position in my group to work with me on Adaptive Online Learning and other topics in Statistical Learning Theory.
The ideal starting date would be the fall of 2020 or early 2021.
A requirement is to have multiple theory papers at COLT/NeurIPS/ICML/JMLR or similar.
If you are interested and are attending NeurIPS next week, then please contact me to arrange to meet up informally at the conference.
To apply, send me your CV and a short denoscription of your background at tim@timvanerven.nl.
Best regards,
Tim
✔️ @ApplyTime
Principal NLP Research Scientist at ACTNext
Overview
ACT is a nonprofit organization helping people achieve educational and workplace success. Our programs are designed to boost lifelong learning in schools and workplaces around the world. Whether it's guiding students along their learning paths, enabling companies to develop their workforce, fostering parent, teacher, and counselor understanding of student progress, guiding job seekers toward career success, or informing policymakers about education and workforce issues. ACT is passionate about making a difference in all we do. Learn more about working at ACT at act.org.
Are you passionate about solving big scientific problems in education
through innovative technology and working in a highly multi-disciplinary collaborative environment? Would you like to know more about how computer vision, affective computing and machine learning are helping create new forms of learning and assessment tools? If this sounds intriguing, then we'd like to talk to you about a role as part of a new ACTNext ACT R&D team tackling a set of problems requiring significant innovation.
More info
✔️ @ApplyTime
Overview
ACT is a nonprofit organization helping people achieve educational and workplace success. Our programs are designed to boost lifelong learning in schools and workplaces around the world. Whether it's guiding students along their learning paths, enabling companies to develop their workforce, fostering parent, teacher, and counselor understanding of student progress, guiding job seekers toward career success, or informing policymakers about education and workforce issues. ACT is passionate about making a difference in all we do. Learn more about working at ACT at act.org.
Are you passionate about solving big scientific problems in education
through innovative technology and working in a highly multi-disciplinary collaborative environment? Would you like to know more about how computer vision, affective computing and machine learning are helping create new forms of learning and assessment tools? If this sounds intriguing, then we'd like to talk to you about a role as part of a new ACTNext ACT R&D team tackling a set of problems requiring significant innovation.
More info
✔️ @ApplyTime
ACT.
Jobs at ACT.
View all Jobs at ACT.. Search, apply or sign up for job alerts at ACT. Talent Network
Master research internship, Paris: Cross-lingual transfer with multi-lingual BERT via linguistically informed fine-tuning
Title: Cross-lingual transfer with multi-lingual BERT via linguistically informed fine-tuning
- Duration: 5-6 months, during the year 2020
- Location: LIMSI, Orsay (south of Paris)
- Supervisor: Caio Corro - http://caio-corro.fr/
- Team: Spoken Language Processing / Traitement Automatique de la Parole
- Contact: caio.corro@limsi.fr
Context
Recently, much attention has been paid to large scale pre-training of context-sensitive representations (or context-sensitive word embeddings), in particular ELMO [1] and BERT [2] models. The main idea is to pre-train the first layers of a neural network on a large amount of unlabeled data before fine-tuning the rest of the network on a downstream task. As such, context-sensitive representations allow to lower annotation cost and improve classification performance on a wide range of tasks.
The multilingual BERT model pre-trains context sensitive representations on a collection of texts in 104 languages instead of texts in a single language. One question that arises is whether we can use the multilingual BERT model for cross-lingual learning,
that is training a model on a subset of these languages (source languages) and testing it on a different subset (target languages). This problem is both important under a research perspective (how can we learn multi-lingual representations of typologically diverse languages?) and under an applied industry perspective (i.e. increase language coverage of NLP-based products at low cost). Previous work observed that cross-lingual transfert based on multi-lingual BERT works best for typological similar languages (i.e. languages with similar word order), which is expected but disappointing [3].
This internship will focus on multilingual dependency parsing with the Universal Dependency treebank https://universaldependencies.org/ . Previous work has considered re-ordering source language sentences with respect to word order in target languages [4]. However, re-ordering is not possible for unsupervised large scale pre-training where syntactic structures is not annotated. A different line of work proposed to force word order statistics at test time using constraints [5], but this method is based on a costly lagrangian optimization procedure and cannot be applied on a per sentence basis. Alternatively, we propose to explore fine-tuning methods for multi-lingual BERT model using a linguistically informed training algorithm, i.e. to use dominant word order information (is the object placed before or after the verb in a given language?) to ensure unsupervised transfer to target languages.
Missions
The successful candidate will develop neural network architectures and training algorithms for cross-lingual generalization of pre-trained context-sensitive representations. The main evaluation task will be cross-lingual dependency parsing. As there are many ways to tackle this problem, the specific approach will be determined by the intern aspiration, which could be for example posterior regularization or latent variable modeling. In a nutshell, the aim is to:
- propose a method for cross-lingual generalization of multi-lingual BERT using typological information;
- evaluate the proposed method on cross-lingual parsing;
- evaluate if results generalize to other tasks, for example cross-lingual named entity recognition.
[1] "Deep Contextualized Word Representations" Matthew Peters et al.
[2] "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding" Jacob Devlin et al.
[3] "How multilingual is Multilingual BERT?" Telmo Pires et al.
[4] "Zero-resource Dependency Parsing: Boosting Delexicalized Cross-lingual Transfer with Linguistic Knowledge" Lauriane Aufrant et al.
[5] "Target Language-Aware Constrained Inference for Cross-lingual Dependency Parsing" Tao Meng et al.
✔️ @ApplyTime
Title: Cross-lingual transfer with multi-lingual BERT via linguistically informed fine-tuning
- Duration: 5-6 months, during the year 2020
- Location: LIMSI, Orsay (south of Paris)
- Supervisor: Caio Corro - http://caio-corro.fr/
- Team: Spoken Language Processing / Traitement Automatique de la Parole
- Contact: caio.corro@limsi.fr
Context
Recently, much attention has been paid to large scale pre-training of context-sensitive representations (or context-sensitive word embeddings), in particular ELMO [1] and BERT [2] models. The main idea is to pre-train the first layers of a neural network on a large amount of unlabeled data before fine-tuning the rest of the network on a downstream task. As such, context-sensitive representations allow to lower annotation cost and improve classification performance on a wide range of tasks.
The multilingual BERT model pre-trains context sensitive representations on a collection of texts in 104 languages instead of texts in a single language. One question that arises is whether we can use the multilingual BERT model for cross-lingual learning,
that is training a model on a subset of these languages (source languages) and testing it on a different subset (target languages). This problem is both important under a research perspective (how can we learn multi-lingual representations of typologically diverse languages?) and under an applied industry perspective (i.e. increase language coverage of NLP-based products at low cost). Previous work observed that cross-lingual transfert based on multi-lingual BERT works best for typological similar languages (i.e. languages with similar word order), which is expected but disappointing [3].
This internship will focus on multilingual dependency parsing with the Universal Dependency treebank https://universaldependencies.org/ . Previous work has considered re-ordering source language sentences with respect to word order in target languages [4]. However, re-ordering is not possible for unsupervised large scale pre-training where syntactic structures is not annotated. A different line of work proposed to force word order statistics at test time using constraints [5], but this method is based on a costly lagrangian optimization procedure and cannot be applied on a per sentence basis. Alternatively, we propose to explore fine-tuning methods for multi-lingual BERT model using a linguistically informed training algorithm, i.e. to use dominant word order information (is the object placed before or after the verb in a given language?) to ensure unsupervised transfer to target languages.
Missions
The successful candidate will develop neural network architectures and training algorithms for cross-lingual generalization of pre-trained context-sensitive representations. The main evaluation task will be cross-lingual dependency parsing. As there are many ways to tackle this problem, the specific approach will be determined by the intern aspiration, which could be for example posterior regularization or latent variable modeling. In a nutshell, the aim is to:
- propose a method for cross-lingual generalization of multi-lingual BERT using typological information;
- evaluate the proposed method on cross-lingual parsing;
- evaluate if results generalize to other tasks, for example cross-lingual named entity recognition.
[1] "Deep Contextualized Word Representations" Matthew Peters et al.
[2] "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding" Jacob Devlin et al.
[3] "How multilingual is Multilingual BERT?" Telmo Pires et al.
[4] "Zero-resource Dependency Parsing: Boosting Delexicalized Cross-lingual Transfer with Linguistic Knowledge" Lauriane Aufrant et al.
[5] "Target Language-Aware Constrained Inference for Cross-lingual Dependency Parsing" Tao Meng et al.
✔️ @ApplyTime
Postdoc Fellowship at the National Institutes of Health - Machine Learning for Computer-Aided Diagnosis and Medical Image Analysis
Hello:
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.
Basic 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.
Desirable Qualifications: 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). Applications should include a CV, brief statement of research interests and three letters of reference. DHHS and NIH are Equal Opportunity Employers.
Application Instructions:
Email application materials to Dr. Ronald Summers at rms@nih.gov.
--
Daniel C. Elton, Ph.D. | Staff Scientist (contractor)
Imaging Biomarkers and Computer-Aided Diagnosis (CAD) Laboratory
Radiology and Imaging Sciences
National Institutes of Health Clinical Center
✔️ @ApplyTime
Hello:
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.
Basic 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.
Desirable Qualifications: 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). Applications should include a CV, brief statement of research interests and three letters of reference. DHHS and NIH are Equal Opportunity Employers.
Application Instructions:
Email application materials to Dr. Ronald Summers at rms@nih.gov.
--
Daniel C. Elton, Ph.D. | Staff Scientist (contractor)
Imaging Biomarkers and Computer-Aided Diagnosis (CAD) Laboratory
Radiology and Imaging Sciences
National Institutes of Health Clinical Center
✔️ @ApplyTime