Postdoctoral Research Fellowship at University of North Carolina at Chapel Hill
Hi everyone!
A postdoctoral research fellowship position at the University of North Carolina-Chapel Hill School of Nursing is open. This position aims to attract a postdoctoral fellow who is interested in symptom sciences, family research, digital health intervention, and health disparities among cancer survivors and their family caregivers. The successful candidate will conduct NIH and DOD funded research focusing on cancer survivorship and multilevel intervention, including but not limited to data collection, data analysis, intervention development and implementation. The research fellow will participate in designing innovative methods such as advanced machine learning and smart designs to provide personalized and user-friendly interventions that have the real-world impacts. These studies provide an excellent opportunity for the research fellow to work within a multidisciplinary research team that will prepare them for further faculty and industry positions.
Successful candidates will be highly motivated, and be able to identify potential problems and develop solutions, be able to plan and carry out research experiments and projects have strong written and oral communication skills, be able to work independently and participate productively as a team member, and be familiar with research methodology and statistical methods.
In addition, the research fellow will have the opportunity to propose research projects that will be suitable for external funding. The research fellow will be encouraged to prepare and submit a career development award proposal as well as other research proposals as appropriate and to lead publications.
If you are interested, please apply here: https://unc.peopleadmin.com/postings/195915. Thank you!
✔️ @ApplyTime
Hi everyone!
A postdoctoral research fellowship position at the University of North Carolina-Chapel Hill School of Nursing is open. This position aims to attract a postdoctoral fellow who is interested in symptom sciences, family research, digital health intervention, and health disparities among cancer survivors and their family caregivers. The successful candidate will conduct NIH and DOD funded research focusing on cancer survivorship and multilevel intervention, including but not limited to data collection, data analysis, intervention development and implementation. The research fellow will participate in designing innovative methods such as advanced machine learning and smart designs to provide personalized and user-friendly interventions that have the real-world impacts. These studies provide an excellent opportunity for the research fellow to work within a multidisciplinary research team that will prepare them for further faculty and industry positions.
Successful candidates will be highly motivated, and be able to identify potential problems and develop solutions, be able to plan and carry out research experiments and projects have strong written and oral communication skills, be able to work independently and participate productively as a team member, and be familiar with research methodology and statistical methods.
In addition, the research fellow will have the opportunity to propose research projects that will be suitable for external funding. The research fellow will be encouraged to prepare and submit a career development award proposal as well as other research proposals as appropriate and to lead publications.
If you are interested, please apply here: https://unc.peopleadmin.com/postings/195915. Thank you!
✔️ @ApplyTime
Peopleadmin
Postdoctoral Research Fellowship
A postdoctoral research fellowship position at the University of North Carolina-Chapel Hill School of Nursing is open. This position aims to attract a postdoctoral fellow who is interested in symptom sciences, family research, digital health intervention…
Postoctoral Research Fellow at the University of Pennsylvania
The Department of Statistics and Data Science of the Wharton School, University of Pennsylvania, is seeking candidates for a Postdoctoral Researcher position under the supervision of Professor Edgar Dobriban. The focus of the research will be in the theoretical foundations of large scale data analysis, and specifically on connections between randomized sketching and statistical inference. The earliest start date is September 1, 2021. The position will continue for up to three years.
The position is designed to be a career-building step for new scholars. The primary focus is for the scholar to develop her/his research program. A competitive stipend will be provided.
Successful candidates will have opportunities to submit papers to top statistics, data science, numerical analysis, optimization, and machine learning journals and conferences. The candidates will also present their research at conferences in these fields.
Qualifications
Candidates should show outstanding capacity for research, and a promising publication record in leading venues in statistics, machine learning, data science, numerical analysis, applied probability, and/or optimization.
Applicants must have a Ph.D. in statistics, computer science, electrical engineering, applied math, or a related field from an accredited institution.
Application Instructions
Please send CV, research statement, and names/e-mail addresses of three potential letter writers to Professor Dobriban at dobriban@wharton.upenn.edu. Applications are reviewed on a rolling basis. Any questions about the position can be sent to Professor Dobriban at dobriban@wharton.upenn.edu
The University of Pennsylvania is an EOE. Minorities / Women / Individuals with disabilities / Protected veterans are encouraged to apply.
--
Edgar Dobriban
Assistant Professor of Statistics & Computer and Information Science
The Wharton School & SEAS, University of Pennsylvania
statistics.wharton.upenn.edu/profile/dobriban
✔️ @ApplyTime
The Department of Statistics and Data Science of the Wharton School, University of Pennsylvania, is seeking candidates for a Postdoctoral Researcher position under the supervision of Professor Edgar Dobriban. The focus of the research will be in the theoretical foundations of large scale data analysis, and specifically on connections between randomized sketching and statistical inference. The earliest start date is September 1, 2021. The position will continue for up to three years.
The position is designed to be a career-building step for new scholars. The primary focus is for the scholar to develop her/his research program. A competitive stipend will be provided.
Successful candidates will have opportunities to submit papers to top statistics, data science, numerical analysis, optimization, and machine learning journals and conferences. The candidates will also present their research at conferences in these fields.
Qualifications
Candidates should show outstanding capacity for research, and a promising publication record in leading venues in statistics, machine learning, data science, numerical analysis, applied probability, and/or optimization.
Applicants must have a Ph.D. in statistics, computer science, electrical engineering, applied math, or a related field from an accredited institution.
Application Instructions
Please send CV, research statement, and names/e-mail addresses of three potential letter writers to Professor Dobriban at dobriban@wharton.upenn.edu. Applications are reviewed on a rolling basis. Any questions about the position can be sent to Professor Dobriban at dobriban@wharton.upenn.edu
The University of Pennsylvania is an EOE. Minorities / Women / Individuals with disabilities / Protected veterans are encouraged to apply.
--
Edgar Dobriban
Assistant Professor of Statistics & Computer and Information Science
The Wharton School & SEAS, University of Pennsylvania
statistics.wharton.upenn.edu/profile/dobriban
✔️ @ApplyTime
Department of Statistics and Data Science
Edgar Dobriban – Department of Statistics and Data Science
Postdoc, RA & Ph.D. student positions in collaborative/federated learning, data valuation, incentive-aware mechanism design & machine unlearning at National University of Singapore
We are hiring postdoctoral fellows and research assistants interested in advancing the state of the art in collaborative/federated/multi-party learning (incentive-aware mechanism design, data valuation, privacy, heterogeneous black-box model fusion) and machine unlearning, with application to trusted data/model sharing for a period of 1 year with possible renewal/extension.
The postdoctoral fellows and research assistants will be based in the School of Computing of the National University of Singapore (NUS) and have the opportunity to collaborate with/co-advise the PhD and undergraduate students in our research group.
For more information on our research group, interests, and recent papers in ICML, NeurIPS, UAI, AISTATS, and AAAI, visit https://www.comp.nus.edu.sg/~lowkh/research.html). In particular, see the tab on "Trusted Model/Data Sharing and Data Valuation".
A recorded seminar on our recent works is also available here: http://youtu.be/IhizVZdUv6k
The postdoctoral fellow, research assistant, and Ph.D. student positions are financially supported by a 4-year AI Singapore research grant award noscriptd "Toward Trustable Model-centric Sharing for Collaborative Machine Learning" (https://ids.nus.edu.sg/TrustedCollabML.html).
For the postdoc positions, a successful candidate should have a Ph.D. in computer science and engineering, machine learning, statistics, math, data science, operations research or other related disciplines. A good publication record in the premier machine learning and AI conferences and/or journals is preferred. He/she must have a strong proficiency in programming.
For the RA position, a successful candidate should have a Bachelor’s degree in computer science and engineering, statistics, math, data science, operations research or other related disciplines from a reputable university and a strong academic track record (especially in math, statistics, and algorithms courses). A good publication record in the premier machine learning and AI conferences and/or journals is a bonus. He/she must have a strong proficiency in programming.
If you are interested to apply, please send a short cover letter describing your suitability for the position, detailed CV with academic ranking (if any) and publication list, a concise denoscription of research interests and future plans, and academic trannoscripts to:
Dr. Bryan Low and See-Kiong Ng
Emails: lo...@comp.nus.edu.sg, ng...@comp.nus.edu.sg
Websites: https://www.comp.nus.edu.sg/~lowkh/research.html, https://ids.nus.edu.sg/TrustedCollabML.html
We will begin reviewing applications for the positions immediately.
--
Regards,
Bryan Low
Associate Professor of Computer Science, National University of Singapore
Director, AI Research & Technology, AI Singapore
✔️ @ApplyTime
We are hiring postdoctoral fellows and research assistants interested in advancing the state of the art in collaborative/federated/multi-party learning (incentive-aware mechanism design, data valuation, privacy, heterogeneous black-box model fusion) and machine unlearning, with application to trusted data/model sharing for a period of 1 year with possible renewal/extension.
The postdoctoral fellows and research assistants will be based in the School of Computing of the National University of Singapore (NUS) and have the opportunity to collaborate with/co-advise the PhD and undergraduate students in our research group.
For more information on our research group, interests, and recent papers in ICML, NeurIPS, UAI, AISTATS, and AAAI, visit https://www.comp.nus.edu.sg/~lowkh/research.html). In particular, see the tab on "Trusted Model/Data Sharing and Data Valuation".
A recorded seminar on our recent works is also available here: http://youtu.be/IhizVZdUv6k
The postdoctoral fellow, research assistant, and Ph.D. student positions are financially supported by a 4-year AI Singapore research grant award noscriptd "Toward Trustable Model-centric Sharing for Collaborative Machine Learning" (https://ids.nus.edu.sg/TrustedCollabML.html).
For the postdoc positions, a successful candidate should have a Ph.D. in computer science and engineering, machine learning, statistics, math, data science, operations research or other related disciplines. A good publication record in the premier machine learning and AI conferences and/or journals is preferred. He/she must have a strong proficiency in programming.
For the RA position, a successful candidate should have a Bachelor’s degree in computer science and engineering, statistics, math, data science, operations research or other related disciplines from a reputable university and a strong academic track record (especially in math, statistics, and algorithms courses). A good publication record in the premier machine learning and AI conferences and/or journals is a bonus. He/she must have a strong proficiency in programming.
If you are interested to apply, please send a short cover letter describing your suitability for the position, detailed CV with academic ranking (if any) and publication list, a concise denoscription of research interests and future plans, and academic trannoscripts to:
Dr. Bryan Low and See-Kiong Ng
Emails: lo...@comp.nus.edu.sg, ng...@comp.nus.edu.sg
Websites: https://www.comp.nus.edu.sg/~lowkh/research.html, https://ids.nus.edu.sg/TrustedCollabML.html
We will begin reviewing applications for the positions immediately.
--
Regards,
Bryan Low
Associate Professor of Computer Science, National University of Singapore
Director, AI Research & Technology, AI Singapore
✔️ @ApplyTime
YouTube
Trusted Data Sharing: Incentivizing Collaboration and Rights to be Forgotten in Machine Learning
Speaker: Dr Bryan Low (https://www.comp.nus.edu.sg/~lowkh/research.html)
Organized as part of 2020 N-CRiPT Public Seminar series: https://ncript.comp.nus.edu.sg/event/n-cript-public-seminar-trusted-data-sharing/
Organized as part of 2020 N-CRiPT Public Seminar series: https://ncript.comp.nus.edu.sg/event/n-cript-public-seminar-trusted-data-sharing/
👍1
Postdoc, RA & Ph.D. student positions in AutoML, Bayesian optimization, Bayesian deep learning & multi-agent RL at National University of Singapore
We are hiring postdoctoral fellows, research assistants, and Ph.D. students interested in advancing the state of the art in learning with less data (AutoML, Bayesian optimization, meta-learning, active learning) and Bayesian deep learning, with applications to multi-agent reinforcement learning, precision agriculture, and advanced manufacturing for a period of 1 year with possible renewal/extension.
The postdoctoral fellows, research assistants, and Ph.D. students will be based in the School of Computing of the National University of Singapore (NUS). The postdoctoral fellows have the opportunity to collaborate with/co-advise the PhD and undergraduate students in our research group.
For more information on our research group, interests, and recent papers in ICML, NeurIPS, UAI, AISTATS, and AAAI, visit https://www.comp.nus.edu.sg/~lowkh/research.html.
A recorded seminar on our recent works is available here: https://www.youtube.com/watch?v=DvE19gy1U0c.
The postdoctoral fellow and research assistant positions are financially supported by multiple 3- to 4-year research grants involving learning with less data, probabilistic machine learning, and multi-agent reinforcement learning.
For the postdoc positions, a successful candidate should have a Ph.D. in computer science, computer engineering, machine learning, statistics, math, data science, operations research or other related disciplines. A good publication record in the premier machine learning and AI conferences and/or journals is preferred. He/she must have a strong proficiency in programming.
For the RA and Ph.D. student positions, a successful candidate should have a Bachelor’s degree in computer science and engineering, statistics, math, data science, operations research or other related disciplines from a reputable university and a strong academic track record (especially in math, statistics, and algorithms courses). A good publication record in the premier machine learning and AI conferences and/or journals is a bonus. He/she must have a strong proficiency in programming.
If you are interested to apply, please send a short cover letter describing your suitability for the position, detailed CV with academic ranking (if any) and publication list, a concise denoscription of research interests and future plans, and academic trannoscripts to:
Dr. Bryan Low
Email: lowkh@comp.nus.edu.sg
Website: https://www.comp.nus.edu.sg/~lowkh/research.html
We will begin reviewing applications for the positions immediately.
--
Regards,
Bryan Low
Associate Professor of Computer Science, National University of Singapore
Director, AI Research, AI Singapore
We are hiring postdoctoral fellows, research assistants, and Ph.D. students interested in advancing the state of the art in learning with less data (AutoML, Bayesian optimization, meta-learning, active learning) and Bayesian deep learning, with applications to multi-agent reinforcement learning, precision agriculture, and advanced manufacturing for a period of 1 year with possible renewal/extension.
The postdoctoral fellows, research assistants, and Ph.D. students will be based in the School of Computing of the National University of Singapore (NUS). The postdoctoral fellows have the opportunity to collaborate with/co-advise the PhD and undergraduate students in our research group.
For more information on our research group, interests, and recent papers in ICML, NeurIPS, UAI, AISTATS, and AAAI, visit https://www.comp.nus.edu.sg/~lowkh/research.html.
A recorded seminar on our recent works is available here: https://www.youtube.com/watch?v=DvE19gy1U0c.
The postdoctoral fellow and research assistant positions are financially supported by multiple 3- to 4-year research grants involving learning with less data, probabilistic machine learning, and multi-agent reinforcement learning.
For the postdoc positions, a successful candidate should have a Ph.D. in computer science, computer engineering, machine learning, statistics, math, data science, operations research or other related disciplines. A good publication record in the premier machine learning and AI conferences and/or journals is preferred. He/she must have a strong proficiency in programming.
For the RA and Ph.D. student positions, a successful candidate should have a Bachelor’s degree in computer science and engineering, statistics, math, data science, operations research or other related disciplines from a reputable university and a strong academic track record (especially in math, statistics, and algorithms courses). A good publication record in the premier machine learning and AI conferences and/or journals is a bonus. He/she must have a strong proficiency in programming.
If you are interested to apply, please send a short cover letter describing your suitability for the position, detailed CV with academic ranking (if any) and publication list, a concise denoscription of research interests and future plans, and academic trannoscripts to:
Dr. Bryan Low
Email: lowkh@comp.nus.edu.sg
Website: https://www.comp.nus.edu.sg/~lowkh/research.html
We will begin reviewing applications for the positions immediately.
--
Regards,
Bryan Low
Associate Professor of Computer Science, National University of Singapore
Director, AI Research, AI Singapore
YouTube
Learning with Less Data Data Efficient Probabilistics ML by Bryan Low
The official channel of the NUS Department of Computer Science
Looking for PhD students and post-doctoral researchers
Dear colleagues and students,
The IDLab research group of the University of Antwerp and imec, has several interesting open positions. We're looking both for enthusiastic PhD students and senior post-doctoral researchers. More specifically, we have the following open positions
PhD Students
PhD Vacancy in Artificial Intelligence for Graph Evolution Prediction: working on GNNs and its application to process control in domains such as chemical engineering, water treatment and HVAC.
PhD Vacancy on Next Generation AI for Perception and Cognition: working on next generation neural network architectures such as spiking neural networks and hyperdimensional computing
PhD Vacancy in Artificial Intelligence for an Automated Lab: automating process control systems in the pharmaceutical sector
Senior researchers
Senior Researcher on Causal Artificial Intelligence: leading a small team of PhD students working on topics such as causal machine learning and relational learning
Artificial Intelligence Project Manager: translating machine learning research to applied projects in collaboration with industry.
All these positions can be found at https://jobs.idlab.uantwerpen.be/
Feel free to forward this mail to anyone that comes to mind.
Thanks in advance,
Steven Latre
steven.latre@uantwerpen.be
--
prof. dr. Steven Latré
Director
at IDlab, University of Antwerp, in collaboration with imec
steven.latre@uantwerpen.be
The Beacon I Sint-Pietersvliet 7 I 2000 Antwerpen I Belgium
✔️ @ApplyTime
🌐 https://applytime.ir
Dear colleagues and students,
The IDLab research group of the University of Antwerp and imec, has several interesting open positions. We're looking both for enthusiastic PhD students and senior post-doctoral researchers. More specifically, we have the following open positions
PhD Students
PhD Vacancy in Artificial Intelligence for Graph Evolution Prediction: working on GNNs and its application to process control in domains such as chemical engineering, water treatment and HVAC.
PhD Vacancy on Next Generation AI for Perception and Cognition: working on next generation neural network architectures such as spiking neural networks and hyperdimensional computing
PhD Vacancy in Artificial Intelligence for an Automated Lab: automating process control systems in the pharmaceutical sector
Senior researchers
Senior Researcher on Causal Artificial Intelligence: leading a small team of PhD students working on topics such as causal machine learning and relational learning
Artificial Intelligence Project Manager: translating machine learning research to applied projects in collaboration with industry.
All these positions can be found at https://jobs.idlab.uantwerpen.be/
Feel free to forward this mail to anyone that comes to mind.
Thanks in advance,
Steven Latre
steven.latre@uantwerpen.be
--
prof. dr. Steven Latré
Director
at IDlab, University of Antwerp, in collaboration with imec
steven.latre@uantwerpen.be
The Beacon I Sint-Pietersvliet 7 I 2000 Antwerpen I Belgium
✔️ @ApplyTime
🌐 https://applytime.ir
Postdoctoral Position in Computational Imaging and Machine Learning
The Department of Radiology at Michigan Medicine of the University of Michigan has an immediate opening at the postdoctoral level for individuals interested in development and application of advanced image-based analytical techniques in the field of thoracic radiology. The ideal candidate would have experience in signal & image processing, computer vision, computational imaging and machine learning applied to medical imaging.
Interested applicants please apply to the advertisement here: http://www.umich.edu/~cgalbanlab/pdf/Postdoc.pdf
Regards,
Sundaresh Ram
✔️ @ApplyTime
The Department of Radiology at Michigan Medicine of the University of Michigan has an immediate opening at the postdoctoral level for individuals interested in development and application of advanced image-based analytical techniques in the field of thoracic radiology. The ideal candidate would have experience in signal & image processing, computer vision, computational imaging and machine learning applied to medical imaging.
Interested applicants please apply to the advertisement here: http://www.umich.edu/~cgalbanlab/pdf/Postdoc.pdf
Regards,
Sundaresh Ram
✔️ @ApplyTime
Two Fully Funded PhD Positions in University of Jyväskylä, Finland
Faculty of Information Technology (cognitive science), University of Jyväskylä, Finland, is looking for two PhD students (fully funded for 2+2 years) in the intersection of computer science and cognitive science.
The positions are in two collaborating projects funded by Academy of Finland. The project "Machines that Understand People" develops RL-based computational cognitive models of human-computer interaction. The project “Appropriate Uncertainty in Manual and Automated Driving” develops computational models of driver’s information sampling.
The successful candidates should have:
- Master in computer science, cognitive science, human-computer interaction, or a related field
- Programming skills (e.g., Python)
- Statistical skills (e.g., Bayesian statistics)
- Interest in the research of reinforcement learning and computational cognitive models
- Motivation to obtain a doctoral degree
- English communication skills
The PhD students will work under the supervision of Dr. Jussi Jokinen and Dr. Tuomo Kujala, as part of Human-Technology Interaction research group (https://www.jyu.fi/it/en/research/research-areas/cognitive-science-and-educational-technology/hti).
Please send your CV, along with a letter of interest, to tuomo.kujala@jyu.fi no later than August 31, 2021. The positions are scheduled to start in September/October 2021.
For more information, please contact tuomo.kujala@jyu.fi or jussi.p.p.jokinen@jyu.fi
✔️ @ApplyTime
Faculty of Information Technology (cognitive science), University of Jyväskylä, Finland, is looking for two PhD students (fully funded for 2+2 years) in the intersection of computer science and cognitive science.
The positions are in two collaborating projects funded by Academy of Finland. The project "Machines that Understand People" develops RL-based computational cognitive models of human-computer interaction. The project “Appropriate Uncertainty in Manual and Automated Driving” develops computational models of driver’s information sampling.
The successful candidates should have:
- Master in computer science, cognitive science, human-computer interaction, or a related field
- Programming skills (e.g., Python)
- Statistical skills (e.g., Bayesian statistics)
- Interest in the research of reinforcement learning and computational cognitive models
- Motivation to obtain a doctoral degree
- English communication skills
The PhD students will work under the supervision of Dr. Jussi Jokinen and Dr. Tuomo Kujala, as part of Human-Technology Interaction research group (https://www.jyu.fi/it/en/research/research-areas/cognitive-science-and-educational-technology/hti).
Please send your CV, along with a letter of interest, to tuomo.kujala@jyu.fi no later than August 31, 2021. The positions are scheduled to start in September/October 2021.
For more information, please contact tuomo.kujala@jyu.fi or jussi.p.p.jokinen@jyu.fi
✔️ @ApplyTime
Informaatioteknologian tiedekunta
Human-Technology Interaction (Cognitive Science)
Tutkimusryhmän sivu
Postdoc at the University of Nebraska-Lincoln
The Cognitive and Affective Neuroscience Lab at the University of Nebraska-Lincoln (PI: Maital Neta) invites applications for a full-time Postdoctoral Researcher (start date negotiable). The postdoc will contribute to NIMH- and NSF-funded research examining individual differences in emotion processing and emotion regulation across the lifespan.
The successful candidate will have completed a PhD in psychology, neuroscience, or a related field and have a strong publication record that includes neuroimaging studies, preferably with a focus on using fMRI to examine theoretically relevant questions in cognitive psychology and emotion in particular. Candidates with substantial prior experience using advanced MRI methods (e.g., resting state MRI, MVPA, network analyses), psychophysiology and/or with eye tracking are uniquely attractive. Strong technical skills are preferred, including competence in several programming environments, and familiarity with programs such as E-prime, R, Matlab, Python, AFNI, SPM, FSL, and Unix is especially valued but not required and otherwise would be learned on the job.
The lab is housed in the Center for Brain, Biology, & Behavior at UNL (http://cb3.unl.edu/), which has a state-of-the-art Brain Imaging Center and a 3T MRI scanner dedicated for research. Beyond having access to the scanner, the postdoctoral fellow will also have access to with EEG/ERP, fNIRS, tDCS, virtual reality, mobile psychophysiology, eye-tracking (many of which can be measured both in and out of the MRI scanner), as well as several other cutting-edge techniques.
The position is available immediately, but the start date can be flexible. We will begin reviewing applications immediately, and continue reviewing them on a rolling basis until the position is filled. Salary is commensurate with experience, and includes health benefits.
To apply, please fill out the application form at https://tinyurl.com/slqmovm. You will need your CV and the contact information for three references. Please also feel free to contact Maital Neta (mneta2@unl.edu) for more information.
✔️ @ApplyTime
The Cognitive and Affective Neuroscience Lab at the University of Nebraska-Lincoln (PI: Maital Neta) invites applications for a full-time Postdoctoral Researcher (start date negotiable). The postdoc will contribute to NIMH- and NSF-funded research examining individual differences in emotion processing and emotion regulation across the lifespan.
The successful candidate will have completed a PhD in psychology, neuroscience, or a related field and have a strong publication record that includes neuroimaging studies, preferably with a focus on using fMRI to examine theoretically relevant questions in cognitive psychology and emotion in particular. Candidates with substantial prior experience using advanced MRI methods (e.g., resting state MRI, MVPA, network analyses), psychophysiology and/or with eye tracking are uniquely attractive. Strong technical skills are preferred, including competence in several programming environments, and familiarity with programs such as E-prime, R, Matlab, Python, AFNI, SPM, FSL, and Unix is especially valued but not required and otherwise would be learned on the job.
The lab is housed in the Center for Brain, Biology, & Behavior at UNL (http://cb3.unl.edu/), which has a state-of-the-art Brain Imaging Center and a 3T MRI scanner dedicated for research. Beyond having access to the scanner, the postdoctoral fellow will also have access to with EEG/ERP, fNIRS, tDCS, virtual reality, mobile psychophysiology, eye-tracking (many of which can be measured both in and out of the MRI scanner), as well as several other cutting-edge techniques.
The position is available immediately, but the start date can be flexible. We will begin reviewing applications immediately, and continue reviewing them on a rolling basis until the position is filled. Salary is commensurate with experience, and includes health benefits.
To apply, please fill out the application form at https://tinyurl.com/slqmovm. You will need your CV and the contact information for three references. Please also feel free to contact Maital Neta (mneta2@unl.edu) for more information.
✔️ @ApplyTime
cb3.unl.edu
UNL | Center for Brain, Biology and Behavior
A funded PhD position is still available in our group to work in an exciting area of ‘Perovskite Nanocrystals for Solar-Driven Electricity and Hydrogen Generation’.
Come and wor #cleanenergy k with us at UNSW Engineering.
Suitable for applicants currently in Australia/New Zealand with a background in #nanotechnology #chemistry #materialsscience
and #devicephysics.
Deadline: 27th August 2021.
More info here: https://research.unsw.edu.au/people/dr-mahesh-suryawanshi
✔️ @ApplyTime
Come and wor #cleanenergy k with us at UNSW Engineering.
Suitable for applicants currently in Australia/New Zealand with a background in #nanotechnology #chemistry #materialsscience
and #devicephysics.
Deadline: 27th August 2021.
More info here: https://research.unsw.edu.au/people/dr-mahesh-suryawanshi
✔️ @ApplyTime
Two postdoctoral fellowships in Statistics (FGV EMAp) Rio de Janeiro, Brazil
Postdoctoral fellowship in Statistics
The School of Applied Mathematics at Fundação Getulio Vargas (FGV EMAp) in Rio de Janeiro, Brazil, invites applications for two postdoctoral fellowships in Statistics beginning no later than December 31st, 2021.
We are looking for early-career researchers to develop innovative research in Statistics and Data Science. Individuals with applied and methodological interests in statistics for large complex data or financial/actuarial statistics. Candidates whose research interests intersect with the research agenda of other members of the department will be given priority.
The successful candidate is expected to develop collaborative research within the department, supporting our ongoing expansion in the area. It is also expected the post holder will collaborate with the members of the group on the application process for external funding. Light teaching duty may be required. Remote applicants will be considered.
Qualifications
The successful candidate is expected to hold a Ph.D. in statistics, or related discipline, by the time of the appointment. We expect the applicant to have an expanding track of publications and a strong potential of publishing in top ranked Statistics journals. The successful candidate will also possess excellent communication and presentation skills.
About us
Getulio Vargas Foundation (FGV) is a distinguished and internationally renowned Brazilian higher-learning institution dedicated to the intellectual development of the nation. The School of Applied Mathematics (EMAp) located in Rio de Janeiro, has as its main goals to contribute with the effort of FGV towards innovation through the use of Mathematics in its numerous areas of application, especially the Applied Social Sciences.
We are a growing department that aspires to be top ranked in Latin America and world-wide. The School of Applied Mathematics currently offers Ph.D., M.Sc., and undergraduate degrees in applied mathematics and Data Science. We also have an ongoing Postdoctoral Fellowship program. In 2020 a research center for Data Sciences was created, boosting investigation in the area.
Application
Academics with appropriate qualifications are kindly invited to send their applications electronically to postdoc.emap@fgv.br, including:
Cover letter which describes your experience, interests and suitability for the position;
Curriculum vitae; and
A list of academic articles showcasing the applicant’s research.
The applicant should also provide at least two reference letters, addressing your research qualifications and accomplishments, to be sent directly to the hiring committee.
Applications (including reference letters) received by August 29, 2021 (extended to September 30, 2021) will receive full consideration.
Informal inquiries can be addressed to Profs. Eduardo Mendes (eduardo.mendes@fgv.br), Rodrigo Targino (rodrigo.targino@fgv.br) and Luiz Max Carvalho (luiz.fagundes@fgv.br).
Salary and Benefits
This position is a 24 months fixed term contract with possibility of extending it for another 12 months. We offer an internationally competitive salary compatible with previous experience and accomplishments.
Further considerations
FGV is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, ethnicity, sex (including gender identity), national origin, disability status, age, sexual orientation, or any other characteristic protected by law. We always welcome nominations and applications from women, members of any minority group, and others who share our passion for building a diverse community that reflects the diversity in our student population.
✔️ @ApplyTime
Postdoctoral fellowship in Statistics
The School of Applied Mathematics at Fundação Getulio Vargas (FGV EMAp) in Rio de Janeiro, Brazil, invites applications for two postdoctoral fellowships in Statistics beginning no later than December 31st, 2021.
We are looking for early-career researchers to develop innovative research in Statistics and Data Science. Individuals with applied and methodological interests in statistics for large complex data or financial/actuarial statistics. Candidates whose research interests intersect with the research agenda of other members of the department will be given priority.
The successful candidate is expected to develop collaborative research within the department, supporting our ongoing expansion in the area. It is also expected the post holder will collaborate with the members of the group on the application process for external funding. Light teaching duty may be required. Remote applicants will be considered.
Qualifications
The successful candidate is expected to hold a Ph.D. in statistics, or related discipline, by the time of the appointment. We expect the applicant to have an expanding track of publications and a strong potential of publishing in top ranked Statistics journals. The successful candidate will also possess excellent communication and presentation skills.
About us
Getulio Vargas Foundation (FGV) is a distinguished and internationally renowned Brazilian higher-learning institution dedicated to the intellectual development of the nation. The School of Applied Mathematics (EMAp) located in Rio de Janeiro, has as its main goals to contribute with the effort of FGV towards innovation through the use of Mathematics in its numerous areas of application, especially the Applied Social Sciences.
We are a growing department that aspires to be top ranked in Latin America and world-wide. The School of Applied Mathematics currently offers Ph.D., M.Sc., and undergraduate degrees in applied mathematics and Data Science. We also have an ongoing Postdoctoral Fellowship program. In 2020 a research center for Data Sciences was created, boosting investigation in the area.
Application
Academics with appropriate qualifications are kindly invited to send their applications electronically to postdoc.emap@fgv.br, including:
Cover letter which describes your experience, interests and suitability for the position;
Curriculum vitae; and
A list of academic articles showcasing the applicant’s research.
The applicant should also provide at least two reference letters, addressing your research qualifications and accomplishments, to be sent directly to the hiring committee.
Applications (including reference letters) received by August 29, 2021 (extended to September 30, 2021) will receive full consideration.
Informal inquiries can be addressed to Profs. Eduardo Mendes (eduardo.mendes@fgv.br), Rodrigo Targino (rodrigo.targino@fgv.br) and Luiz Max Carvalho (luiz.fagundes@fgv.br).
Salary and Benefits
This position is a 24 months fixed term contract with possibility of extending it for another 12 months. We offer an internationally competitive salary compatible with previous experience and accomplishments.
Further considerations
FGV is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, ethnicity, sex (including gender identity), national origin, disability status, age, sexual orientation, or any other characteristic protected by law. We always welcome nominations and applications from women, members of any minority group, and others who share our passion for building a diverse community that reflects the diversity in our student population.
✔️ @ApplyTime
Forwarded from Deep Gravity
PhD position at the university of Neuchatel
We are looking for a PhD student to join our group on reinforcement learning and decision making at the University of Neuchatel, Switzerland ( https://www.unine.ch/ ). We are particularly interested in candidates with a strong mathematical background. Prior research experience as documented by your Masters thesis will be an additional bonus. Although any area in the intersection of machine learning, statistics and artificial intelligence may be considered, we are primarily looking for a student with a sincere interest in one or more of the following areas:
1. Reinforcement learning
2. Privacy (e.g. differential privacy)
3. Fairness in machine learning.
Examples of our group's past and current research can be found on arxiv: https://arxiv.org/search/?searchtype=author&query=Dimitrakakis%2C+C. The student will have the opportunity to visit and work with other group members at the University of Oslo, Norway ( https://www.mn.uio.no/ifi/english/people/aca/chridim/index.html ) and Chalmers University of Technology, Sweden ( http://www.cse.chalmers.se/~chrdimi/ ). The position is available from 1 Februrary 2022.
For further information, please contact me directly at christos.dimitrakakis@gmail.com with the subject 'PhD Neuchatel'.
🔭 @DeepGravity
We are looking for a PhD student to join our group on reinforcement learning and decision making at the University of Neuchatel, Switzerland ( https://www.unine.ch/ ). We are particularly interested in candidates with a strong mathematical background. Prior research experience as documented by your Masters thesis will be an additional bonus. Although any area in the intersection of machine learning, statistics and artificial intelligence may be considered, we are primarily looking for a student with a sincere interest in one or more of the following areas:
1. Reinforcement learning
2. Privacy (e.g. differential privacy)
3. Fairness in machine learning.
Examples of our group's past and current research can be found on arxiv: https://arxiv.org/search/?searchtype=author&query=Dimitrakakis%2C+C. The student will have the opportunity to visit and work with other group members at the University of Oslo, Norway ( https://www.mn.uio.no/ifi/english/people/aca/chridim/index.html ) and Chalmers University of Technology, Sweden ( http://www.cse.chalmers.se/~chrdimi/ ). The position is available from 1 Februrary 2022.
For further information, please contact me directly at christos.dimitrakakis@gmail.com with the subject 'PhD Neuchatel'.
🔭 @DeepGravity
Université de Neuchâtel
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