Stanford Postdoc in Machine Learning and Public Policy
Professors Daniel Ho and Jacob Goldin invite applications for a postdoctoral scholar focused on the intersection of machine learning, statistics, and public policy. The work would focus on a high-impact collaboration with the Internal Revenue Service to build a more effective and equitable tax system. This is a 2-year position, with the potential of renewal. Some or all of the work may be conducted remotely. For more information, see the RegLab website.
We are searching for outstanding individuals with strong research backgrounds. Experience with research in one or more of the following areas is desirable: machine learning, algorithmic fairness, sequential decision making (e.g., active learning). A Ph.D. degree in Computer Science, Economics, Statistics or a related field is required.
Successful candidates should be prepared to send two letters of reference from your previous research supervisors and collaborators on request. The review of applications will begin immediately and will continue until the position is filled.
Apply online at: https://forms.gle/iVz8HVCxJeUVPNxQ9
Stanford University is an affirmative action and equal opportunity employer, committed to increasing the diversity of its workforce.
--
Christine Tsang
Executive Director | Regulation, Evaluation, and Governance Lab (RegLab)
Stanford Law School | 559 Nathan Abbott Way | Stanford, CA 94305
✔️ @ApplyTime
Professors Daniel Ho and Jacob Goldin invite applications for a postdoctoral scholar focused on the intersection of machine learning, statistics, and public policy. The work would focus on a high-impact collaboration with the Internal Revenue Service to build a more effective and equitable tax system. This is a 2-year position, with the potential of renewal. Some or all of the work may be conducted remotely. For more information, see the RegLab website.
We are searching for outstanding individuals with strong research backgrounds. Experience with research in one or more of the following areas is desirable: machine learning, algorithmic fairness, sequential decision making (e.g., active learning). A Ph.D. degree in Computer Science, Economics, Statistics or a related field is required.
Successful candidates should be prepared to send two letters of reference from your previous research supervisors and collaborators on request. The review of applications will begin immediately and will continue until the position is filled.
Apply online at: https://forms.gle/iVz8HVCxJeUVPNxQ9
Stanford University is an affirmative action and equal opportunity employer, committed to increasing the diversity of its workforce.
--
Christine Tsang
Executive Director | Regulation, Evaluation, and Governance Lab (RegLab)
Stanford Law School | 559 Nathan Abbott Way | Stanford, CA 94305
✔️ @ApplyTime
ELLIS Pan-European PhD Program: 100+ PhD positions in machine learning and related fields
Apply by November 15, 2021 to join the ELLIS PhD Program in 2022 – Details at ellis.eu/phd-postdoc
The ELLIS PhD program has launched its second round of central recruitment and is now accepting applications. A key element of the ELLIS initiative, the program's central aim is to foster and educate the best talent in machine learning and related research areas by pairing outstanding students from across the globe with leading researchers in Europe. The program also offers a variety of networking and training activities. Each PhD student is co-supervised by two ELLIS scientists based in different European countries. Over the course of their degree, students complete a mandatory exchange of at least six months at their co-advisor's lab. One of the advisors may also come from industry, in which case the student will collaborate closely with the private sector partner and spend their exchange conducting research at an industrial lab.
Research areas include (but are not limited to) the following machine learning-driven research fields:
Machine Learning Algorithms
Machine Learning Theory
Optimization
Deep Learning
Interactive and Online Learning
Reinforcement Learning and Control
Computer Vision
Computer Graphics
Robotics
Human Computer Interaction
Natural Language Processing
Causality
Interpretability and Fairness
Robust and Trustworthy Machine Learning
Quantum and Physics-based Machine Learning
Symbolic Machine Learning
Computational Neuroscience
Earth and Climate Sciences
Bioinformatics
Health
You can watch our introductory video here: https://www.youtube.com/watch?v=kWXNpnxkfg0.
The deadline for applications is November 15, 2021. Interested candidates should apply online through the ELLIS application portal. For more detailed information on the program, specific research areas, and the application process, please consult the call for applications: https://ellis.eu/news/ellis-phd-program-call-for-applications-deadline-november-15-2021.
✔️ @ApplyTime
Apply by November 15, 2021 to join the ELLIS PhD Program in 2022 – Details at ellis.eu/phd-postdoc
The ELLIS PhD program has launched its second round of central recruitment and is now accepting applications. A key element of the ELLIS initiative, the program's central aim is to foster and educate the best talent in machine learning and related research areas by pairing outstanding students from across the globe with leading researchers in Europe. The program also offers a variety of networking and training activities. Each PhD student is co-supervised by two ELLIS scientists based in different European countries. Over the course of their degree, students complete a mandatory exchange of at least six months at their co-advisor's lab. One of the advisors may also come from industry, in which case the student will collaborate closely with the private sector partner and spend their exchange conducting research at an industrial lab.
Research areas include (but are not limited to) the following machine learning-driven research fields:
Machine Learning Algorithms
Machine Learning Theory
Optimization
Deep Learning
Interactive and Online Learning
Reinforcement Learning and Control
Computer Vision
Computer Graphics
Robotics
Human Computer Interaction
Natural Language Processing
Causality
Interpretability and Fairness
Robust and Trustworthy Machine Learning
Quantum and Physics-based Machine Learning
Symbolic Machine Learning
Computational Neuroscience
Earth and Climate Sciences
Bioinformatics
Health
You can watch our introductory video here: https://www.youtube.com/watch?v=kWXNpnxkfg0.
The deadline for applications is November 15, 2021. Interested candidates should apply online through the ELLIS application portal. For more detailed information on the program, specific research areas, and the application process, please consult the call for applications: https://ellis.eu/news/ellis-phd-program-call-for-applications-deadline-november-15-2021.
✔️ @ApplyTime
ELLIS
PhD & Postdoc Program
The ELLIS PhD & Postdoc Program links top students with leading AI researchers, offering co-supervision and exchanges within Europe.
PhD positions at the Gatsby Unit
If you are interested in pursuing a PhD in machine learning or theoretical neuroscience at the Gatsby Computational Neuroscience Unit in London, applications for our programme are now open. Please send us your application by 14th November 2021. Apply here: https://www.ucl.ac.uk/gatsby/study-and-work/phd-programme/applications
The Gatsby Unit is part of University College London and focuses on machine learning and theoretical neuroscience. We specialize in research and research training: We have a PhD programme and postdoctoral trainees, but no undergraduate or MSc programme.
Our PhD programme provides a rigorous preparation for a research career. Although each student eventually chooses an advisor, the programme is highly interactive, and the unit functions more like a single large research group loosely divided into subgroups than a regular university department. Many leading researchers in both machine learning and neuroscience have studied or worked in the Unit. Overall, about 2/3 of our alumni are in academia, many are faculty members at the world's leading universities, others have founded companies (including DeepMind), and almost all are active in research. You can see our network of alumni here: https://www.ucl.ac.uk/gatsby/greater-gatsby
Full funding is available to all students, regardless of nationality. Gatsby PhD studentships cover the cost of tuition at the appropriate rate, and include a tax-free stipend, presently £24,000 per annum. The Unit also welcomes applications from students with pre-secured funding or who are currently soliciting other scholarship/studentships.
Official information on the programme can be found here:
https://www.ucl.ac.uk/gatsby/study-and-work/phd-programme
We particularly encourage applications from underrepresented groups.
Questions should be directed to admissions@gatsby.ucl.ac.uk
✔️ @ApplyTime
If you are interested in pursuing a PhD in machine learning or theoretical neuroscience at the Gatsby Computational Neuroscience Unit in London, applications for our programme are now open. Please send us your application by 14th November 2021. Apply here: https://www.ucl.ac.uk/gatsby/study-and-work/phd-programme/applications
The Gatsby Unit is part of University College London and focuses on machine learning and theoretical neuroscience. We specialize in research and research training: We have a PhD programme and postdoctoral trainees, but no undergraduate or MSc programme.
Our PhD programme provides a rigorous preparation for a research career. Although each student eventually chooses an advisor, the programme is highly interactive, and the unit functions more like a single large research group loosely divided into subgroups than a regular university department. Many leading researchers in both machine learning and neuroscience have studied or worked in the Unit. Overall, about 2/3 of our alumni are in academia, many are faculty members at the world's leading universities, others have founded companies (including DeepMind), and almost all are active in research. You can see our network of alumni here: https://www.ucl.ac.uk/gatsby/greater-gatsby
Full funding is available to all students, regardless of nationality. Gatsby PhD studentships cover the cost of tuition at the appropriate rate, and include a tax-free stipend, presently £24,000 per annum. The Unit also welcomes applications from students with pre-secured funding or who are currently soliciting other scholarship/studentships.
Official information on the programme can be found here:
https://www.ucl.ac.uk/gatsby/study-and-work/phd-programme
We particularly encourage applications from underrepresented groups.
Questions should be directed to admissions@gatsby.ucl.ac.uk
✔️ @ApplyTime
Gatsby Computational Neuroscience Unit
Applications
Two Senior Research Associate jobs at Oxford University in Computer Vision and Natural Language Processing
Oxford University invites applications for two postdoctoral positions (Grade 8: £42,149 - £50,296 p.a.), one with a specialism in Computer Vision and the other with a specialism in Natural Language Processing.
Deadline: Applications due noon November 9th, 2021.
The Senior Research Associate in Machine Learning (Computer Vision) will engage in internationally leading research in analysis of complex, heterogenous data at scale; he/she will bring state of the art machine learning to the heart of geospatial data analytics specifically for multi-spectral satellite imagery. The Researcher will develop and pioneer new Bayesian/deep machine learning techniques for big data, remote sensing, multi-sensor data fusion and interpretable estimation to improve the quality, coverage and transparency of geospatial datasets, mapping and characterising the most polluting industries world-wide.
The Senior Research Associate in Machine Learning (Natural Language Processing) will engage in internationally leading research in analysis of complex, unstructured text data at scale; he/she will bring state-of-the-art natural language processing to the heart of sustainable finance. The Researcher will develop and pioneer new Bayesian/deep machine learning techniques in natural language understanding, including text-mining, to improve the quality, coverage and transparency of datasets, characterising the most polluting industries world-wide.
The researchers will work in a team of machine learning experts within the Oxford Sustainable Finance Programme (OxSFP). The machine learning team is led by Dr Steven Reece, who has transitioned to Geography from Engineering Science following 30 years research in fundamental machine learning and, recently, leading a group focussing on applications in disaster management and environmental protection. The researcher’s work will have a strong impact component and is in collaboration with The Alan Turing Institute, the UK’s national institute for artificial intelligence and data science, and the Satellite Applications Catapult, a UK technology and innovation company which aims to support UK industry by accelerating the growth of satellite applications.
The successful candidate’s work will produce open asset-level datasets with commensurate levels of uncertainty to help project partners and stakeholders to align finance with sustainability, a necessary condition for tackling the environmental and social challenges facing humanity, to manage the risks and capture the opportunities associated with the transition to global environmental sustainability.
Link to full job denoscription and application instructions: https://my.corehr.com/pls/uoxrecruit/erq_jobspec_version_4.display_form?p_company=10&p_internal_external=E&p_display_in_irish=N&p_process_type=&p_applicant_no=&p_form_profile_detail=&p_display_apply_ind=Y&p_refresh_search=Y&p_recruitment_id=153202
✔️ @ApplyTime
Oxford University invites applications for two postdoctoral positions (Grade 8: £42,149 - £50,296 p.a.), one with a specialism in Computer Vision and the other with a specialism in Natural Language Processing.
Deadline: Applications due noon November 9th, 2021.
The Senior Research Associate in Machine Learning (Computer Vision) will engage in internationally leading research in analysis of complex, heterogenous data at scale; he/she will bring state of the art machine learning to the heart of geospatial data analytics specifically for multi-spectral satellite imagery. The Researcher will develop and pioneer new Bayesian/deep machine learning techniques for big data, remote sensing, multi-sensor data fusion and interpretable estimation to improve the quality, coverage and transparency of geospatial datasets, mapping and characterising the most polluting industries world-wide.
The Senior Research Associate in Machine Learning (Natural Language Processing) will engage in internationally leading research in analysis of complex, unstructured text data at scale; he/she will bring state-of-the-art natural language processing to the heart of sustainable finance. The Researcher will develop and pioneer new Bayesian/deep machine learning techniques in natural language understanding, including text-mining, to improve the quality, coverage and transparency of datasets, characterising the most polluting industries world-wide.
The researchers will work in a team of machine learning experts within the Oxford Sustainable Finance Programme (OxSFP). The machine learning team is led by Dr Steven Reece, who has transitioned to Geography from Engineering Science following 30 years research in fundamental machine learning and, recently, leading a group focussing on applications in disaster management and environmental protection. The researcher’s work will have a strong impact component and is in collaboration with The Alan Turing Institute, the UK’s national institute for artificial intelligence and data science, and the Satellite Applications Catapult, a UK technology and innovation company which aims to support UK industry by accelerating the growth of satellite applications.
The successful candidate’s work will produce open asset-level datasets with commensurate levels of uncertainty to help project partners and stakeholders to align finance with sustainability, a necessary condition for tackling the environmental and social challenges facing humanity, to manage the risks and capture the opportunities associated with the transition to global environmental sustainability.
Link to full job denoscription and application instructions: https://my.corehr.com/pls/uoxrecruit/erq_jobspec_version_4.display_form?p_company=10&p_internal_external=E&p_display_in_irish=N&p_process_type=&p_applicant_no=&p_form_profile_detail=&p_display_apply_ind=Y&p_refresh_search=Y&p_recruitment_id=153202
✔️ @ApplyTime
Fellow applications for Georgia Tech/Emory Computational Neural Engineering Training Program
Georgia Tech/Emory invite you to apply to become a Fellow in our NIH/NIBIB Computational Neural Engineering Training Program (CNTP)! Fellows receive full stipend and tuition for two years to support rotations and foster cross-disciplinary collaborative training. The CNTP aims to train the next generation of researchers at the intersection of computational neuroscience, neural engineering, data science, and clinical neurophysiology.
Central to our mission is our core belief that just as the diversity among cells, circuits, and networks is critical for navigating a complex and ever-changing world, diversity in the background, experiences, and expertise among our team members is key to understanding and interacting with the brain. The CNTP seeks diversity in the recruiting of our fellows, scholars, and training faculty, equity among the members of our diverse team, and to create an inclusive community where everyone feels welcome and heard.
Training components include new coursework (“Clinical Experience for Engineers”), seminars, innovation forums, professional development meetings, and community retreats. Overall, the CNTP creates novel opportunities to gain experience in science, engineering and clinical domains, resulting in an exceptional and unique training experience. More information on the CNTP is here: https://sites.gatech.edu/cntp/.
Fellow applications are solicited from admitted applicants to one of the four participating PhD programs linked below (PhD in BME, ECE, Bioe or ML). Fellows must be US Citizens or Permanent Residents. If you are interested in joining the CNTP, you must first apply to one of those programs. Deadlines vary, beginning December 1, 2021. Detailed application instructions: https://sites.gatech.edu/cntp/how-to-apply/.
Please contact Dr. Rozell at crozell@gatech.edu with any questions.
Graduate program application assistance
Current CNTP trainees are offering graduate application assistance to provide feedback on essays and give guidance on potentially relevant faculty. You can request assistance by filling out the form below before November 8, 2021:
https://docs.google.com/forms/d/e/1FAIpQLSefcaCnxG_CLQnUvw6Mvgo2Q2zzrnhDx_dXNwdgrHyvHGqIpQ/viewform?usp=sf_link
Participating PhD programs
PhD in Biomedical Engineering at GT/Emory (due 12/1/2021)
https://bme.gatech.edu/bme/georgia-tech-emory-bme-phd-program
PhD in Electrical & Computer Engineering at GT (due 12/16/2021)
https://www.ece.gatech.edu/graduate-admissions
PhD in Bioengineering at GT with BME or ECE home school (deadline is from home school)
https://bioengineering.gatech.edu/
PhD in Machine Learning at GT with BME or ECE home school (deadline is from home school)
http://ml.gatech.edu/phd
✔️ @ApplyTime
Georgia Tech/Emory invite you to apply to become a Fellow in our NIH/NIBIB Computational Neural Engineering Training Program (CNTP)! Fellows receive full stipend and tuition for two years to support rotations and foster cross-disciplinary collaborative training. The CNTP aims to train the next generation of researchers at the intersection of computational neuroscience, neural engineering, data science, and clinical neurophysiology.
Central to our mission is our core belief that just as the diversity among cells, circuits, and networks is critical for navigating a complex and ever-changing world, diversity in the background, experiences, and expertise among our team members is key to understanding and interacting with the brain. The CNTP seeks diversity in the recruiting of our fellows, scholars, and training faculty, equity among the members of our diverse team, and to create an inclusive community where everyone feels welcome and heard.
Training components include new coursework (“Clinical Experience for Engineers”), seminars, innovation forums, professional development meetings, and community retreats. Overall, the CNTP creates novel opportunities to gain experience in science, engineering and clinical domains, resulting in an exceptional and unique training experience. More information on the CNTP is here: https://sites.gatech.edu/cntp/.
Fellow applications are solicited from admitted applicants to one of the four participating PhD programs linked below (PhD in BME, ECE, Bioe or ML). Fellows must be US Citizens or Permanent Residents. If you are interested in joining the CNTP, you must first apply to one of those programs. Deadlines vary, beginning December 1, 2021. Detailed application instructions: https://sites.gatech.edu/cntp/how-to-apply/.
Please contact Dr. Rozell at crozell@gatech.edu with any questions.
Graduate program application assistance
Current CNTP trainees are offering graduate application assistance to provide feedback on essays and give guidance on potentially relevant faculty. You can request assistance by filling out the form below before November 8, 2021:
https://docs.google.com/forms/d/e/1FAIpQLSefcaCnxG_CLQnUvw6Mvgo2Q2zzrnhDx_dXNwdgrHyvHGqIpQ/viewform?usp=sf_link
Participating PhD programs
PhD in Biomedical Engineering at GT/Emory (due 12/1/2021)
https://bme.gatech.edu/bme/georgia-tech-emory-bme-phd-program
PhD in Electrical & Computer Engineering at GT (due 12/16/2021)
https://www.ece.gatech.edu/graduate-admissions
PhD in Bioengineering at GT with BME or ECE home school (deadline is from home school)
https://bioengineering.gatech.edu/
PhD in Machine Learning at GT with BME or ECE home school (deadline is from home school)
http://ml.gatech.edu/phd
✔️ @ApplyTime
GT/Emory Computational Neural-Engineering Training Program
CNTP Homepage
NIH Sponsored T32 Training Grant
5-Year MSc/PhD program in Computational Neuroscience in Tuebingen
International Max Planck Research School: The Mechanisms of Mental
Function and Dysfunction
5-Year combined MSc/PhD program
The Max Planck Institute for Biological Cybernetics, the Hertie Institute
for Clinical Brain Research and the University of Tübingen invite students
from all over the world to apply for their interdisciplinary 5-year combined
MSc/PhD program leading to a PhD in Neuroscience. Full funding is
available for top-ranked applicants.
We are seeking talented, curious and open-minded scientists with strong
backgrounds in neuroscience, biomedical sciences, computational science,
applied mathematics, statistics, artificial intelligence, or
engineering. Successful candidates will possess a burning aspiration to
shape the future of neuroscience and the ability to thrive in a
fast-paced, interdisciplinary, environment.
The application deadline is 30th November 2021. Please visit:
https://www.kyb.tuebingen.mpg.de/imprs-mmfd
https://www.neuroschool-tuebingen.de/about-imprs/
for more details and information about applying.
The MSc/PhD program is a collaboration between the Max Planck Institute
for Biological Cybernetics, the Hertie Institute for Clinical Brain
Research and the University of Tübingen. It is closely affiliated with
the renowned Graduate Training Centre of Neuroscience, the centerpiece
of neuroscience training in Tübingen. Students (who should have been
awarded a Bachelor's degree by September 2022) will receive a broad
interdisciplinary training in neuroscience, including expert teaching by
international renowned scientists and individual and intensive
mentoring.
Potential research topics cover a variety of fields in systems
neuroscience, cognitive and behavioral neuroscience, computational
neuroscience, translational and clinical neuroscience as well as
cellular and molecular neuroscience.
Teaching and research are conducted in English.
✔️ @ApplyTime
International Max Planck Research School: The Mechanisms of Mental
Function and Dysfunction
5-Year combined MSc/PhD program
The Max Planck Institute for Biological Cybernetics, the Hertie Institute
for Clinical Brain Research and the University of Tübingen invite students
from all over the world to apply for their interdisciplinary 5-year combined
MSc/PhD program leading to a PhD in Neuroscience. Full funding is
available for top-ranked applicants.
We are seeking talented, curious and open-minded scientists with strong
backgrounds in neuroscience, biomedical sciences, computational science,
applied mathematics, statistics, artificial intelligence, or
engineering. Successful candidates will possess a burning aspiration to
shape the future of neuroscience and the ability to thrive in a
fast-paced, interdisciplinary, environment.
The application deadline is 30th November 2021. Please visit:
https://www.kyb.tuebingen.mpg.de/imprs-mmfd
https://www.neuroschool-tuebingen.de/about-imprs/
for more details and information about applying.
The MSc/PhD program is a collaboration between the Max Planck Institute
for Biological Cybernetics, the Hertie Institute for Clinical Brain
Research and the University of Tübingen. It is closely affiliated with
the renowned Graduate Training Centre of Neuroscience, the centerpiece
of neuroscience training in Tübingen. Students (who should have been
awarded a Bachelor's degree by September 2022) will receive a broad
interdisciplinary training in neuroscience, including expert teaching by
international renowned scientists and individual and intensive
mentoring.
Potential research topics cover a variety of fields in systems
neuroscience, cognitive and behavioral neuroscience, computational
neuroscience, translational and clinical neuroscience as well as
cellular and molecular neuroscience.
Teaching and research are conducted in English.
✔️ @ApplyTime
www.kyb.tuebingen.mpg.de
IMPRS Program
two postdoc openings at the SBL
Dear All,
we have two exciting postdoc positions in the lab. If any of them speaks to you, don't hesitate to apply (see link in the attached pictures or pdf), and if you know someone potentially interested, don't hesitate to spread the news!
Thank you
valeria
--
"A scientist, first of all, is a person."
Valeria Gazzola, PhD, Department Head
(http://scholar.google.nl/citations?user=4VtrQcMAAAAJ&hl=en&oi=ao)
Social Brain Laboratory
Netherlands Institute for Neuroscience
Royal Netherlands Academy of Arts and Sciences
Meibergdreef 47, 1105 BA Amsterdam, NL
Phone: + 31 20 5661717 Fax: + 31 20 5666121
✔️ @ApplyTime
Dear All,
we have two exciting postdoc positions in the lab. If any of them speaks to you, don't hesitate to apply (see link in the attached pictures or pdf), and if you know someone potentially interested, don't hesitate to spread the news!
Thank you
valeria
--
"A scientist, first of all, is a person."
Valeria Gazzola, PhD, Department Head
(http://scholar.google.nl/citations?user=4VtrQcMAAAAJ&hl=en&oi=ao)
Social Brain Laboratory
Netherlands Institute for Neuroscience
Royal Netherlands Academy of Arts and Sciences
Meibergdreef 47, 1105 BA Amsterdam, NL
Phone: + 31 20 5661717 Fax: + 31 20 5666121
✔️ @ApplyTime
Multiple job openings (PhD, Postdoc and Lab technician positions) are available in the working group/department of Li Zhaoping in the Max Planck Institute for Biological Cybernetics and/or University of Tuebingen. Please follow the links below for the open positions and application procedure. We look forward to receiving your application.
• Lab Mechatronics / Programming Assistant
https://jobs.tue.mpg.de/en/programs/132
• PhD position in Human Psychophysics with TMS and/or EEG
https://jobs.tue.mpg.de/en/programs/147
• Postdoctoral position in Human Psychophysics with TMS and/or EEG https://jobs.tue.mpg.de/en/programs/148
• Postdoctoral position in Human Psychophysics with High field and/or 3T fMRI https://jobs.tue.mpg.de/en/programs/149
• PhD position in Zebrafish Neuroscience
https://jobs.tue.mpg.de/en/programs/150
• Postdoctoral position in Zebrafish Neuroscience
https://jobs.tue.mpg.de/en/programs/151
Informal inquiries can be addressed to jobs.li@tuebingen.mpg.de.
More information can be obtained from http://www.lizhaoping.org/jobs.html
✔️ @ApplyTime
• Lab Mechatronics / Programming Assistant
https://jobs.tue.mpg.de/en/programs/132
• PhD position in Human Psychophysics with TMS and/or EEG
https://jobs.tue.mpg.de/en/programs/147
• Postdoctoral position in Human Psychophysics with TMS and/or EEG https://jobs.tue.mpg.de/en/programs/148
• Postdoctoral position in Human Psychophysics with High field and/or 3T fMRI https://jobs.tue.mpg.de/en/programs/149
• PhD position in Zebrafish Neuroscience
https://jobs.tue.mpg.de/en/programs/150
• Postdoctoral position in Zebrafish Neuroscience
https://jobs.tue.mpg.de/en/programs/151
Informal inquiries can be addressed to jobs.li@tuebingen.mpg.de.
More information can be obtained from http://www.lizhaoping.org/jobs.html
✔️ @ApplyTime
Stanford Interdisciplinary Postdoc opportunity
A Stanford School of Medicine research team is looking for a talented postdoctoral fellow to work on several cutting-edge, computational research projects related to neuroscience and clinical care in the Department of Anesthesiology, Perioperative and Pain Medicine. Projects include, but are not limited to, clinical research to evaluate anesthetic depth using state-of-the-art electrophysiological techniques, assessment of existing brain function anesthetic depth monitors, and computational projects assessing and modelling features of perioperative care on patient outcomes. Candidates must hold a Ph.D. before time of employment and competitive skillsets include signal processing on time series data (including but not limited to spectral analysis, nonlinear dynamics, and network science), experience working with clinical research data, and advanced knowledge of biostatistics. Ideal candidates will have experience with MATLAB and/or Python programming, superb oral and written communication skills, and excellent time management.
Please send CV along with a cover letter introducing yourself to Dr. David Drover (ddrover@stanford.edu). Please include [sysNeuro anesPostdoc] in the subject line.
Cheers,
Sarah
✔️ @ApplyTime
A Stanford School of Medicine research team is looking for a talented postdoctoral fellow to work on several cutting-edge, computational research projects related to neuroscience and clinical care in the Department of Anesthesiology, Perioperative and Pain Medicine. Projects include, but are not limited to, clinical research to evaluate anesthetic depth using state-of-the-art electrophysiological techniques, assessment of existing brain function anesthetic depth monitors, and computational projects assessing and modelling features of perioperative care on patient outcomes. Candidates must hold a Ph.D. before time of employment and competitive skillsets include signal processing on time series data (including but not limited to spectral analysis, nonlinear dynamics, and network science), experience working with clinical research data, and advanced knowledge of biostatistics. Ideal candidates will have experience with MATLAB and/or Python programming, superb oral and written communication skills, and excellent time management.
Please send CV along with a cover letter introducing yourself to Dr. David Drover (ddrover@stanford.edu). Please include [sysNeuro anesPostdoc] in the subject line.
Cheers,
Sarah
✔️ @ApplyTime
Fully funded robotics Ph.D. positions in Fall 2022 at George Mason University
Application due December 1 2021!
The RobotiXX lab at the Department of Computer Science, George Mason University in the Washington, D.C. area (https://www2.gmu.edu/), is looking for self-motivated Ph.D. students in the area of robotics starting Fall 2022. The candidate will be supported with full tuition and stipends.
At RobotiXX lab, we perform robotics research at the intersection of motion planning and machine learning, with a specific focus on deployable field robotics. Any candidate with relevant experience in robotics, motion planning, and machine learning is encouraged to apply. Hands-on knowledge in robotics hardware, field experience, and a good publication record is strongly preferred.
The selected candidates will conduct independent research to develop highly capable and intelligent mobile robots that are robustly deployable in the real world with minimal human supervision, and publish papers in top-tier robotics conferences and journals. To apply, please visit George Mason University's admission website (https://www2.gmu.edu/admissions-aid) and send a single PDF of the following documents to Dr. Xuesu Xiao, incoming Assistant Professor in Fall 2022 (xiao@cs.utexas.edu): 1. cover letter, 2. curriculum vitae, 3. trannoscript, 4. three references, 5. relevant publications, 6. other relevant materials, with the subject line “[jobs] YOUR AFFILIATION - YOUR NAME”.
For more information, please see the lab’s research statement (https://www.cs.utexas.edu/~xiao/xuesu_website_files/Research_Statement.pdf), YouTube Channel (https://www.youtube.com/channel/UCCePdJzWg35eml4WRGkX3GQ/videos), and website (https://www.cs.utexas.edu/~xiao/).
Thanks
Xuesu Xiao
-----------------------
Xuesu Xiao, Ph.D.
--
Incoming Assistant Professor (Fall 2022)
Department of Computer Science
George Mason University
--
Roboticist, The Everyday Robot Project
X, The Moonshot Factory
xuesuxiao@google.com
https://x.company/projects/everyday-robots/
--
Research Affiliate
Department of Computer Science
The University of Texas at Austin
xiao@cs.utexas.edu
https://www.cs.utexas.edu/~xiao/
✔️ @ApplyTime
Application due December 1 2021!
The RobotiXX lab at the Department of Computer Science, George Mason University in the Washington, D.C. area (https://www2.gmu.edu/), is looking for self-motivated Ph.D. students in the area of robotics starting Fall 2022. The candidate will be supported with full tuition and stipends.
At RobotiXX lab, we perform robotics research at the intersection of motion planning and machine learning, with a specific focus on deployable field robotics. Any candidate with relevant experience in robotics, motion planning, and machine learning is encouraged to apply. Hands-on knowledge in robotics hardware, field experience, and a good publication record is strongly preferred.
The selected candidates will conduct independent research to develop highly capable and intelligent mobile robots that are robustly deployable in the real world with minimal human supervision, and publish papers in top-tier robotics conferences and journals. To apply, please visit George Mason University's admission website (https://www2.gmu.edu/admissions-aid) and send a single PDF of the following documents to Dr. Xuesu Xiao, incoming Assistant Professor in Fall 2022 (xiao@cs.utexas.edu): 1. cover letter, 2. curriculum vitae, 3. trannoscript, 4. three references, 5. relevant publications, 6. other relevant materials, with the subject line “[jobs] YOUR AFFILIATION - YOUR NAME”.
For more information, please see the lab’s research statement (https://www.cs.utexas.edu/~xiao/xuesu_website_files/Research_Statement.pdf), YouTube Channel (https://www.youtube.com/channel/UCCePdJzWg35eml4WRGkX3GQ/videos), and website (https://www.cs.utexas.edu/~xiao/).
Thanks
Xuesu Xiao
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Xuesu Xiao, Ph.D.
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Incoming Assistant Professor (Fall 2022)
Department of Computer Science
George Mason University
--
Roboticist, The Everyday Robot Project
X, The Moonshot Factory
xuesuxiao@google.com
https://x.company/projects/everyday-robots/
--
Research Affiliate
Department of Computer Science
The University of Texas at Austin
xiao@cs.utexas.edu
https://www.cs.utexas.edu/~xiao/
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PhD Position on Continual Reinforcement Learning at the University of Southern Denmark | DL: 15 Nov 2021
Hi everyone,
I have a vacant position for a PhD thesis project at the University of Southern Denmark. We are located in Odense, a lively university town of c.a. 180k inhabitants. The topic is probabilistic dynamics modeling with application to continual reinforcement learning. Please find the job ad under the link below:
https://www.sdu.dk/en/service/ledige_stillinger/1173438
I look forward to the applications of those who are interested.
The application deadline is 15 November 2021.
Best regards,
Melih Kandemir
https://melihkandemir.github.io
✔️ @ApplyTime
Hi everyone,
I have a vacant position for a PhD thesis project at the University of Southern Denmark. We are located in Odense, a lively university town of c.a. 180k inhabitants. The topic is probabilistic dynamics modeling with application to continual reinforcement learning. Please find the job ad under the link below:
https://www.sdu.dk/en/service/ledige_stillinger/1173438
I look forward to the applications of those who are interested.
The application deadline is 15 November 2021.
Best regards,
Melih Kandemir
https://melihkandemir.github.io
✔️ @ApplyTime
sdu
* - SDU
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