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Flatiron Research Fellows (Post-Docs), Center for Computational Neuroscience, Flatiron Institute
by Matthew Turner 04 Nov '21

04 Nov '21

Flatiron Research Fellows (Post-Docs), Center for Computational Neuroscience <https://www.simonsfoundation.org/flatiron/center-for-computational-neurosci…>, Flatiron Institute New York, New York ORGANIZATIONAL OVERVIEW The Simons Foundation is a private foundation established in 1994 in New York City. With assets of approximately $2 billion and an annual grants and programs budget of $230 million, the foundation is dedicated to advancing the frontiers of research in mathematics and the basic sciences. The Flatiron Institute is a major, new internal scientific unit of the Simons Foundation, focused on the computational aspects of a wide range of basic science. The mission of the Flatiron Institute is to advance scientific research through computational methods, including theory, modeling, simulation and data analysis. The Flatiron Institute currently consists of five centers: the Center for Computational Astrophysics (CCA); the Center for Computational Biology (CCB); the Center for Computational Quantum Physics (CCQ); the Center for Computational Mathematics (CCM); and the Center for Computational Neuroscience (CCN). The Institute staff is composed of research scientists at various stages of their careers from recent Ph.D.s through senior scientists, software engineers and support staff. We host a vigorous visitor program and interact regularly with scientists from neighboring institutions. POSITION SUMMARY Applications are invited for Flatiron Research Fellowships (FRF) at the Center for Computational Neuroscience. The CCN FRF program offers the opportunity for postdoctoral research in areas that have strong synergy with one or more of the existing research groups at CCN or other centers at the Flatiron Institute. CCN FRF’s will be assigned a primary mentor from a CCN research group or project, though affiliations and collaborations with other research groups within CCN and throughout the Flatiron Institute are encouraged. In addition to carrying out an independent research program, Flatiron Research Fellows are expected to: disseminate their results through scientific presentations, publications, and software release, collaborate with other members of the CCN or Flatiron Institute, and participate in the scientific life of the CCN and Flatiron Institute by attending seminars, colloquia, and group meetings. Flatiron Research Fellows may have the opportunity to organize workshops and to mentor graduate and undergraduate students. The mission of CCN is to develop theories, models, and computational methods that deepen our knowledge of brain function — both in health and in disease. CCN takes a “systems" neuroscience approach, building models that are motivated by fundamental principles, that are constrained by properties of neural circuits and responses, and that provide insights into perception, cognition and behavior. This cross-disciplinary approach not only leads to the design of new model-driven scientific experiments, but also encapsulates current functional descriptions of the brain that can spur the development of new engineered computational systems, especially in the realm of machine learning. CCN currently has research groups in computational vision, neural circuits and algorithms, neuroAI and geometry, and statistical analysis of neural data; interested candidates should review the CCN public website <https://www.simonsfoundation.org/flatiron/center-for-computational-neurosci…> for specific information on CCN’s research areas. Review of applications for positions starting between July and October 2022 will begin in mid-January 2022. Application Materials: - Cover letter (optional); - Curriculum Vitae with bibliography; - Research statement of no more than three pages describing past work and proposed research program. Applicants are encouraged to discuss the broad impact of the past and proposed research on computational neuroscience. Applicants should also indicate the primary CCN group(s) with which they’d seek to conduct research, and any desired affiliation with other Flatiron Centers. - Three (3) letters of recommendation submitted confidentially by direct email to ccnjobs(a)simonsfoundation.org Selection Criteria: Applicants must have a PhD in a related field or expect to receive their PhD before the start of the appointment. Applications will be evaluated based on 1) past research accomplishments 2) proposed research program 3) synergy of applicant’s expertise and research proposal topic with existing CCN staff and research programs. Education: - PhD in computational neuroscience or a relevant technical field such as electrical engineering, machine learning, statistics, physics, or applied math. Related Skills: - Flexible multi-disciplinary mindset; - Strong interest and experience in the scientific study of the brain; - Demonstrated abilities in analysis, software and algorithm development, modeling and/or scientific simulation; - Ability to do original and outstanding research in neuroscience; - Ability to work well independently as well as in a collaborative team environment. FRF positions are two-year appointments and are generally renewed for a third year, contingent on performance. FRF receive a research budget and have access to the Flatiron Institute’s powerful scientific computing resources. FRF may be eligible for subsidized housing within walking distance of the CCN. THE SIMONS FOUNDATION'S DIVERSITY COMMITMENT Many of the greatest ideas and discoveries come from a diverse mix of minds, backgrounds and experiences, and we are committed to cultivating an inclusive work environment. The Simons Foundation actively seeks a diverse applicant pool and encourages candidates of all backgrounds to apply. We provide equal opportunities to all employees and applicants for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, genetic disposition, neurodiversity, disability, veteran status or any other protected category under federal, state and local law. Application portal: https://simonsfoundation.wd1.myworkdayjobs.com/en-US/simonsfoundationcareer… Matthew B. Turner Manager for Center Administration | Center for Computational Neuroscience Pronouns: he/him/his *FLATIRON INSTITUTE* 162 Fifth Avenue Suite 308 New York, NY 10010 917.363.1095 *mobile* *simonsfoundation.org/flatiron/ <http://simonsfoundation.org/flatiron/>*

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Postdoc Fellowship in Data Science in Göttingen, Germany
by Ecker, Alexander 04 Nov '21

04 Nov '21

The Campus Institute Data Science (CIDAS) at the University of Göttingen invites applications for two fellowships for outstanding young scientists to implement their own innovative research agenda in the field of Data Science and Artificial Intelligence. CIDAS promotes campus-wide interdisciplinary exchange and activities in the field of data science. The application deadline is Sunday, November 14th, 2021. In case of questions contact Alexander Ecker: ecker(a)cs.uni-goettingen.de *Funding Objectives:* CIDAS would like to support young scientists at an early stage of their career to develop independent projects and to create a perspective to work independently for several years at the Göttingen Campus in the field of Data Science. In particular, the collaboration between methodological, theoretical researchers and applied scientists at the Göttingen Campus and within CIDAS should be promoted. The applications should show a career perspective for the applicants and open a path to scientific independence and own third-party funding. *Who can apply:* Outstanding young scientists who are in the final phase of their PhD (last year) or early postdoc phase (maximum 2 years after the PhD) with an idea for their own research project in the field of Data Science. This can be in the fundamentals of Data Science, applied Data Science, or in the social science aspects of Data Science. This requires a planned collaboration with at least one member of CIDAS. Other collaborations with groups outside CIDAS are also possible and encouraged. If the applicant is not already a CIDAS member, he/she will be accepted into CIDAS upon approval of the application. The position can be used in particular for preparatory work for a subsequent application, e.g. for a junior research group. *Scope of funding:* Two fellowships will be awarded. The funding includes €75,000 each, which can be used, for example, to finance the applicant's own position. *Documents to be submitted:* 1. Description of the research idea (max. 5 pages), incl.: - Clearly defined content-related goals, comprehensible time schedule - Possible perspectives after the project, career perspectives, possibly plan for external funding - Planned collaboration with CIDAS members and other scientists - Innovation of the application 2. Curriculum vitae 3. Letter of recommendation from the supervisor or mentor, including a workplace (incl. infrastructure) commitment for the period to be funded Deadline: Sunday, November 14th, 2021 Application by email to: cidas(a)uni-goettingen.de -- Alexander Ecker Professor of Data Science Department of Computer Science • Campus Institute Data Science University of Göttingen • Max Planck Inst. for Dynamics and Self-Organization Goldschmidtstr. 1 • room 2.137 • 37077 Göttingen https://eckerlab.org • @alxecker • +49 551 39-21272

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PhD position at the Institute for Theoretical Physics, Goethe University Frankfurt
by Claudius Gros 04 Nov '21

04 Nov '21

PhD position at the Institute for Theoretical Physics, Goethe University Frankfurt Applications are invited for a fully funded PhD position at the Institute for Theoretical Physics, Goethe University Frankfurt, Germany Fields: neurosciences, complex systems theory Application deadline: Dec 15, 2021 Supervisor: Prof. Dr. Claudius Gros We are developing new models and generative principles for complex systems, using a range of toolsets from dynamical systems theory, game theory, and the neurosciences. Examples are self-generated gaits for animals and robotic systems, criticality in autonomous networks, as well as Covid-19 modeling. Several subjects are available for the announced PhD thesis, depending on the background of the successful candidate. The work will include analytical investigations and numerical simulations. The candidates should have a Diploma/Master in physics with an excellent academic track record and good computational skills. Experience or strong interest in the fields of complex systems, dynamical systems theory, game theory and/or artificial or biological cognitive systems is expected. The degree of scientific research experience is expected to be on the level of a German Diploma/Master. The appointment will start in spring 2022, for three years. Interested applicants should submit a curriculum vitae and a list of publications to the address below. Prof. Claudius Gros Institute for Theoretical Physics Goethe University Frankfurt Max-von-Laue-Str. 1 60438 Frankfurt am Main, Germany cgr(a)itp.uni-frankfurt.de http://www.itp.uni-frankfurt.de/~gros General information on the University of Frankfurt and its employment policy: With its around 46,000 students and 4,600 employees, the Goethe University in Frankfurt is the largest university in the state of Hessen and an internationally renowned, important regional employer. Numerous quality and performance oriented internal reforms have been initiated in the recent years. The reorganized campuses for natural sciences and humanities offer an ideal environment for research and education. Since 2008, the Goethe University is a foundation under public law and enjoys full administrative autonomy.  The fixed-term employment of the academic staff is subject to the provisions of the Temporary Science Employment Law and the Hessian Higher Education Act. The University advocates gender equality and therefore strongly encourages women to apply. People with disabilities are given preference if equally qualified. -- ### ### Prof. Dr. Claudius Gros ### http://itp.uni-frankfurt.de/~gros ### ### Complex and Adaptive Dynamical Systems, A Primer ### A graduate-level textbook, Springer (2008/10/13/15) ### ### Life for barren exoplanets: The Genesis project ### https://link.springer.com/article/10.1007/s10509-016-2911-0 ###

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Faculty position in Data Science and Neuroengineering at Boston University
by Laura Lewis 03 Nov '21

03 Nov '21

Dear colleagues, Forwarding the ad for our department's open position for an Assistant Professor: The College of Engineering at Boston University has embarked on a bold new strategic plan that will pursue excellence and impact along convergent and collaborative research themes while remaining committed to our institutional values regarding diversity, equity, and inclusion. The College anticipates two openings for tenure-track faculty positions at the level of Assistant Professor, one focusing on the convergent theme: Data Science in Neuroengineering. We are seeking a candidate whose research develops or uses methods from data science to advance knowledge of neuroscience in health and disease. Topics may include computational neuroscience, neurosignal processing, machine learning, image processing, artificial intelligence, or, more broadly, data science techniques in neuroscience. The ideal candidate will have a strong publication record in this convergent research theme and will be able to form links among the neuro- and systems-engineering strengths of the College’s Departments of Biomedical Engineering and Electrical and Computer Engineering, as well as the University’s strengths in the Data- and Neuro-Sciences. To apply: https://academicjobsonline.org/ajo/jobs/19046

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Postdoctoral position to study circuit mechanisms of adaptive learning at Dartmouth College
by Alireza Soltani 03 Nov '21

03 Nov '21

The Computational and Cognitive Neuroscience Lab (CCNL) at Dartmouth College has an opening for an NIH-funded postdoctoral position to work on an exciting project on circuit mechanisms of reward-based learning under uncertainty. The project involves computational modeling and data analyses (behavioral and calcium imaging) in close collaboration with Alicia Izquierdo's lab at UCLA. Initial appointment is for one year with opportunity for renewal. The position is open to start immediately, but applications will be considered until the position is filled. A few recent relevant papers include: 1. Soltani A, Izquierdo A (2019). Adaptive Learning under Expected and Unexpected Uncertainty. Nature Reviews Neuroscience, 20(10): 635–644 2. Farashahi S, Donahue C, Hayden B, Lee D, Soltani A (2019). Flexible Combination of Reward Information across Primates. Nature Human Behaviour, 3: 1215–1224 3. Stolyarova A, Rakhshan M, Peters MA, Lau H, Soltani A, Izquierdo A (2019). Contributions of Anterior Cingulate Cortex and Basolateral Amygdala in Decision Confidence and Learning under Uncertainty. Nature Communications, 10:4704 4. Spitmaan MM, Seo H, Lee D, Soltani A (2020). Multiple Timescales of Neural Dynamics and Integration of Task-relevant Signals across Cortex. Proceedings of the National Academy of Sciences, 117 (36), 22522-22531 5. Trepka E, Spitmaan MM, Bari BA, Costa VD, Cohen JY, Soltani A (2021). Novel entropy-based metrics for predicting choice behavior based on local response to reward. Nature Communications (Accepted) [available on bioRxiv, 2021.05.20.445009v1] For more recent publications from the lab please visit http://ccnl.dartmouth.edu. Interested individuals should contact Alireza Soltani (soltani(a)dartmouth.edu) with their CV. Alireza Soltani, Ph.D. Associate Professor Department of Psychological and Brain Sciences Dartmouth College, NH Alireza.Soltani(a)Dartmouth.edu http://ccnl.dartmouth.edu Phone: 603-646-2998 Office: Moore 356

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BCI Un-Conference: Submission open
by Anja Meunier 02 Nov '21

02 Nov '21

Dear colleagues, registration and abstract submission for the 3rd BCI Un-Conference is now open [1]. Abstract submissions are text-only. The length and format of the submissions are up to the authors - use whatever format you consider best for attracting up-votes! Important dates: - Submission deadline: December 3rd, 2021 at 11:59 pm (CET) - Voting period: December 6th, 2021 - December 12th, 2021 at 11:59 pm (CET) - BCI-UC event: January 27th, 2022, from 03:00 pm to 09:00 pm (CET) We will invite the authors of the top-voted abstracts to present at the un-conference. The 3rd BCI-UC will feature keynotes by Cynthia Chestek (University of Michigan) [2] and Thorsten Zander (TU Brandenburg) [3]. BCI-UC is an online un-conference that provides rapid dissemination of novel research results in the BCI community. Participants can submit abstracts to apply for 20 minutes presentation slots. Abstracts are not reviewed by a program committee. Rather, all registered participants can vote on which of the submitted abstracts they would like to see presented at the un-conference. Because the BCI-UC does not publish conference proceedings, submitted abstracts can report novel as well as already published work. Registration and attendance are free of charge. Presentations of the 1st and 2nd BCI-UC can be re-watched at [4] and [5]. All presentations will be streamed via Crowdcast [6] and can be accessed free of charge. Join us in supporting this novel community-driven dissemination of research results! The BCI-UC committee: Moritz Grosse-Wentrup Anja Meunier Philipp Raggam Jiachen Xu Links: [1] https://bciunconference.univie.ac.at/register-vote/ [2] https://scholar.google.com/citations?user=36sxAZEAAAAJ&hl=de [3] https://scholar.google.com/citations?hl=en&user=0E49HxYAAAAJ [4] https://bciunconference.univie.ac.at/past-events/1st-bci-uc/ [5] https://bciunconference.univie.ac.at/past-events/2nd-bci-uc/ [6] https://www.crowdcast.io/

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Postdoc position in Computational and Systems Neuroscience at Research Center Jülich, Germany
by Martina Reske 02 Nov '21

02 Nov '21

The working group Statistical Neuroscience at INM-6 Computational and Systems Neuroscience<https://www.fz-juelich.de/inm/inm-6/EN/Home/home_node_INM6.html> at Research Center Juelich, Germany, led by Sonja Grün<https://www.fz-juelich.de/SharedDocs/Personen/INM/INM-6/EN/staff/Gruen_Sonj…> develops statistical methods for the analysis of experimental electrophysiological data from massively parallel electrophysiological recordings and leads the development of open source software tools for the analysis of activity data and validation of models on the population level. The department aims to fill a postdoctoral position that is responsible for the analysis of massively parallel spike and LFP data acquired in a collaborative project with CNRS-AMU, Marseille. Your Job: • Analysis of massively parallel spike and LFP data from the Vision for Action project (visuo-motor integration across areas) • Adaptation of machine learning algorithms and/or further development of methods for the analysis of these neuronal multichannel data • Development of methods for quantifying the relationship between spike patterns and LFP/ECoG data • Optimization and adaptation of neuronal network model in NEST for the comparison of experimental and simulated activity data • Implementation of data analysis tools in Python and integration of the codes into the shared analysis library Elephant • Contribution to the data analysis pipeline, under FAIR principles • Cooperation with experimental collaboration partners • Integration of the work into Ebrains / HBP • Presentation of project results at international conferences • Scientific and administrative project coordination • Support in the supervision of PhD students Your Profile: • MSc in physics, data science, mathematics or computer science; PhD in computational neuroscience, applied mathematics, physics or related • Detailed knowledge of neuroscientific concepts, especially in neuronal dynamics, statistical analysis of neuronal activity and dynamics • Expertise in network modelling at different spatial levels • Experience with large-scale data-science activities and scientific programming, especially Python • Fluent in spoken and written English • Experience in scientific publishing in a related field • Proactive working style, confident appearance and communication skills, high social competence and ability to work cooperatively in a team The position is initially for a fixed term of 2 Jahre years. Salary and benefits in conformity with the provisions of the Collective Agreement for the Civil Service (TVöD, salary grade 13-14). FZ Jülich promotes equal opportunities and diversity in its employment relations. We also welcome applications from disabled persons. Please apply via our recruitment system<https://www.fz-juelich.de/portal/EN/Careers/application/_node.html?cms_hre_…> under reference number: 2021-323. Martina Reske -- Dr. Martina Reske Scientific Coordinator Institute of Neuroscience and Medicine (INM-6) Computational and Systems Neuroscience & Institute for Advanced Simulation (IAS-6) Theoretical Neuroscience Jülich Research Centre and JARA Jülich, Germany Work +49.2461.611916 Work Cell +49.151.26156918 Fax +49.2461.619460 www.csn.fz-juelich.de<http://www.csn.fz-juelich.de> ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ Forschungszentrum Juelich GmbH 52425 Juelich Sitz der Gesellschaft: Juelich Eingetragen im Handelsregister des Amtsgerichts Dueren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Volker Rieke Geschaeftsfuehrung: Prof. Dr.-Ing. Wolfgang Marquardt (Vorsitzender), Karsten Beneke (stellv. Vorsitzender), Prof. Dr. Astrid Lambrecht, Prof. Dr. Frauke Melchior ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------

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The Gatsby Unit PhD programme
by Maneesh Sahani 02 Nov '21

02 Nov '21

Applications for the 2022 PhD Programme in theoretical neuroscience or machine learning at the Gatsby Computational Neuroscience Unit are currently open. Please send us your application by 14th November 2021 following the link on this page: https://www.ucl.ac.uk/gatsby/study-and-work/phd-programme/applications The Gatsby Unit is a research centre at University College London focusing on theoretical and computational neuroscience, computational statistics, machine learning and artificial intelligence; threads that are drawn together by our focus on the mathematical foundations of adaptive intelligent behaviour. 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 here. Overall, about 2/3 of our alumni are in academia, many of them 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. Further 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(a)gatsby.ucl.ac.uk

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Master in Brain and Cognition, Barcelona
by Ruben Moreno Bote 02 Nov '21

02 Nov '21

Enrollment period for the Master in Brain and Cognition open! For Comp Neuro lovers! https:/https://www.upf.edu/web/mbc Why our master? (1) Barcelona, (2) Albert Compte + Gustavo Deco + Alex Hyafil + Klaus Wimmer + myself (Ruben Moreno-Bote) + top others, (3) hands-on teaching, with a 2-trimesters long project, (4) 2 new courses: "The Neural Basis of Memory" by Compte, and "The Brain in Action, Decision Making" by myself (5) highly international students (80% from abroad) + in English + highly competitive (accept only 25, typically from a list of 120 candidates) -- Rubén Moreno Bote Serra Húnter & ICREA Academia Professor Center for Brain and Cognition & Dept. of Information and Communications Technologies University Pompeu Fabra Campus Ciutadella c\ Ramon Trias Fargas, 25-27 Mercè Rodoreda building, 3th floor (room 24.331) 08005 Barcelona, Spain https://www.upf.edu/web/tcn https://twitter.com/morenobote <https://twitter.com/morenobote?lang=ca>

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job: machine learning research scientist at NIMH
by Francisco Pereira 02 Nov '21

02 Nov '21

## HIRING: machine learning research scientist The Machine Learning Team at the National Institute of Mental Health (NIMH) in Bethesda, MD, has an open position for a machine learning research scientist. The NIMH is the leading federal agency for research on mental disorders and neuroscience, and part of the National Institutes of Health (NIH). ## About the NIMH Machine Learning Team Our mission is to help NIMH scientists use machine learning methods to address research problems in clinical and cognitive psychology and neuroscience. These range from identifying biomarkers for aiding diagnoses to creating and testing models of mental processes in healthy subjects. Our overarching goal is to use machine learning to improve every aspect of the scientific effort, from helping discover or develop theories to generating actionable results. We work with many different data types, including very large brain imaging datasets from various imaging modalities, behavioral data, and picture and text corpora. We have excellent computational resources, both of our own (tens of high-end GPUs for deep learning, several large servers) and shared within the NIH (a cluster with hundreds of thousands of CPUs, and hundreds of GPUs). As a machine learning research group, we develop new methods and publish in the main machine learning conferences (e.g. NeurIPS and ICLR), as well as in psychology and neuroscience journals. Many of our problems require devising research approaches that combine imaging and non-imaging data, and leveraging structured knowledge resources (databases, scientific literature, etc) to generate explanations and hypotheses. You can find more about our work and recent publications at https://cmn.nimh.nih.gov/mlt ## About the position We are seeking candidates who are capable of combining machine learning, statistical, and domain-specific computational tools to solve practical data analysis challenges (e.g. designing experiments, generating and testing statistical hypotheses, training and interpreting predictive models, and developing novel models and methods). Additionally, candidates should be capable of visualizing and communicating findings to a broad scientific audience, as well as explaining the details of relevant methods to researchers in a variety of domains. Desirable experience that is not required, but will be considered very favorably: - deep learning - reinforcement learning - Bayesian statistical modelling - other types of modelling of human/animal learning and decision-making - neuroimaging data processing/ analysis (any MRI modality, MEG, or EEG) - other types of neural data (e.g. neural recording, calcium imaging) in the context of substantial research projects, ideally having led to submitted or published articles. Finally, you should have demonstrable experience programming in languages currently used in data-intensive, scientific computing, such as Python, MATLAB or R. Experience with handling large datasets in high performance computing settings is also very valuable. Although this position requires a Ph.D. in a STEM discipline, we will consider applicants from a variety of backgrounds, as their research experience is the most important factor. Backgrounds of team members include computer science, statistics, mathematics, and biomedical engineering. This is an ideal position for someone who wants to establish a research career in method development and applications driven by scientific and clinical needs. Given our access to a variety of collaborators and large or unique datasets, there is ample opportunity to match research interests with novel research problems. We also maintain collaborations outside of the NIH, driven by our own research interests or community impact. If you would like to be considered for this position, please send francisco.pereira(a)nih.gov a CV, with your email serving as cover letter. We especially encourage applications from members of underrepresented groups in the machine learning research community. If you already have a research statement, please feel free to send that as well. There is no need for reference letters at this stage. Other inquiries are also welcome. Thank you for your attention and interest!

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