- Comp-neuro - lists.cnsorg.org

Postdoctoral Position in Deep Learning/Computer Vision with a Focus on 2D Pose Estimation

by Majid Mohajerani

Position Overview: The Mohajerani lab (https://douglas.research.mcgill.ca/majid-mohajerani/) at McGill University is seeking individuals with expertise and experience in video analysis to fill a postdoctoral position that will span three years, ideally starting in November-December 2023. The Postdoctoral position will be based in the vibrant city of Montreal, offering an exceptional quality of life with its rich cultural diversity, culinary delights, and dynamic arts scene. As part of this role, you will work at McGill University, known for its world-class research and academic excellence, providing an intellectually stimulating and inspiring environment for your career growth. The preferred candidate for this Postdoctoral opportunity should hold a Ph.D. in deep learning, computer vision, engineering, or a related field, along with a distinguished research track record. A solid foundation in machine learning, artificial intelligence, and data mining is essential. Proficiency in programming, analytical problem-solving skills, and strong organizational capabilities are prerequisites. Previous hands-on experience with deep neural networks is obligatory. We are searching for a dedicated researcher who thrives on tackling challenges and possesses expertise and enthusiasm for developing video analysis techniques utilizing deep learning methodologies. The recruited candidate will be responsible for conducting research within the PREMIERE project and for participating in the related Work Package activities. The successful candidate must possess a collaborative spirit, as this role involves cooperation with multiple institutions and investigators. Key qualifications: - Strong expertise in deep learning frameworks (e.g., TensorFlow, PyTorch, or Keras). - Demonstrated expertise in applying Recurrent Neural Networks (RNNs), Transformers for temporal sequence analysis, or hybrid models such as Convolutional-LSTM architectures. - Experience in research and/or development for action recognition, body pose and motion estimation, multi-objects tracking, activity recognition, scene understanding, etc. - Expert knowledge of the principles, algorithms, and tools of deep learning, including models, training strategies, training dataset building, loss functions, quality metrics, etc. - Excellent communication and collaboration skills. How to Apply: If you’re passionate about machine learning and want to work in a dynamic and exciting environment, please apply with your resume and a cover letter describing your relevant experience and why you’re the right fit for this role. We strive to ensure that our team is diverse, equitable, and inclusive. All qualified applicants, including women and members of visible minority groups, are welcome to apply. The application review will start on Oct 15th till the positions are filled. If you meet all the requirements, please fill out the following form. https://docs.google.com/forms/d/e/1FAIpQLSe6jDyhrjyE8nFVSokgn3vWpzEjfLhUi83…

Sept. 15, 2023

Tenure track faculty position Cognition and Cognitive Neuroscience Psychology at UMass Amherst

by Tejas Savalia

Dear all, The Department of Psychological and Brain Sciences at the University of Massachusetts, Amherst (http://www.umass.edu/pbs/) is inviting applications for a tenure track, academic year, faculty position at the Assistant Professor level in its Cognition and Cognitive Neuroscience Psychology program, starting in Fall 2024. We are seeking outstanding applicants with expertise in any area of cognitive psychology or cognitive neuroscience, including interdisciplinary fields connected to cognitive psychology, whose work complements and broadens existing strengths in our program. We are known for interdisciplinary and cross-area collaborations and innovation. The program has current strengths in attention, decision-making, psycholinguistics, and mathematical modeling, with connections to our Behavioral Neuroscience, Clinical Psychology, Developmental Science, and Social Psychology programs. Across the university, our faculty have strong connections to Linguistics, Information and Computer Sciences, and Speech, Language, and Hearing Sciences, as well as the Initiative in Cognitive Science, the Computational and Social Science Institute, the Institute for Diversity Sciences, and the Institute for Applied Life Sciences. The Department is interested in candidates who have demonstrated the ability to contribute to the inclusive excellence and diversity mission of the department, college, and university in research, teaching, and/or outreach. Requirements - Applicants must have a Ph.D. in Cognitive Psychology or a closely related field at the time of appointment. - A developing record of demonstrated excellence in research consistent with an early career stage. - Strong methodological skills and a theoretically-based research program. - Demonstrated ability or strong promise of extramural funding. - A strong commitment to undergraduate education, graduate training and mentoring, and diversity and inclusion. About UMass Amherst UMass Amherst, the Commonwealth's flagship campus, is a nationally ranked public research university offering a full range of undergraduate, graduate and professional degrees. The University sits on nearly 1,450-acres in the scenic Pioneer Valley of Western Massachusetts and offers a rich cultural environment in a bucolic setting close to major urban centers. In addition, the University is part of the Five Colleges (including Amherst College, Hampshire College, Mount Holyoke College, and Smith College), which adds to the intellectual energy of the region. Application Instructions Along with the application, please submit a cover letter, curriculum vitae, statement of research interests, statement of teaching philosophy, statement of contributions and future plans to diversity, equity and inclusion (see below), samples of representative research papers, and contact information for three (3) professional references. We will begin to review applications on October 1, 2023, and will continue to accept applications until the position is filled. Please submit materials online to: http://careers.massachusetts.edu/cw/en-us/job/520191?lApplicationSubSourceI… As part of our commitment to supporting our multicultural community, we seek an individual with a demonstrated commitment to diversity and one who will understand and embrace university initiatives and aspirations. The statement of contributions to diversity, equity, and inclusion should identify past experiences and future goals. These contributions may result from lived experiences, scholarships, and/or mentoring, teaching, and outreach activities. (https://www.cns.umass.edu/diversity-equity-inclusion) The University is committed to active recruitment of a diverse faculty and student body. The University of Massachusetts is an Affirmative Action/Equal Opportunity Employer of women, minorities, protected veterans, and individuals with disabilities and encourages applications from these and other protected group members. Because broad diversity is essential to an inclusive climate and critical to the University’s goals of achieving excellence in all areas, we will holistically assess the many qualifications of each applicant and favorably consider an individual’s record working with students and colleagues with broadly diverse perspectives, experiences, and backgrounds in educational, research or other work activities. We will also favorably consider experience overcoming or helping others overcome barriers to an academic career and degree. Best, Tejas Savalia

Sept. 15, 2023

Fwd: CFP: UniReps Workshop on Unifying Representations in Neural Models, NeurIPS 2023, DEADLINE 04 Oct

by Clementine Domine

We are thrilled to announce the first edition of the UniReps Workshop on Unifying Representations in Neural Models <https://unireps.org/>! To be held on Dec 15, 2023 at NeurIPS 2023 <https://nips.cc/>, New Orleans, USA. Our workshop aims to explore the emergence of similar representations from diverse neural models, both artificial and biological, when exposed to similar stimuli. We will investigate this phenomenon's reasons, conditions, and methods and explore the potential for unifying these representations into a shared framework. Additionally, we will delve into exciting applications such as model merging, stitching, and reusing independently trained modules. Our primary objective is to foster collaboration and idea exchange among Machine Learning, Neuroscience, and Cognitive Science researchers. We aim to create a platform for interdisciplinary discussions and collaborations by bringing together experts from diverse backgrounds. *Check our Call For Papers <https://unireps.org/call-for-papers/> below. * *For any additional information check our website <https://unireps.org/>, Twitter profile <https://twitter.com/unireps>, Slack workspace <https://join.slack.com/t/unirepsunifyi-stf5976/shared_invite/zt-22vr60uon-G…>, or contact us at unireps.organizers(a)gmail.com <unireps.organizers(a)gmail.com>.* Call For Papers Neural models, whether in biological or artificial systems, tend to learn similar representations when exposed to similar stimuli. This phenomenon has been observed in various scenarios, e.g., when individuals are exposed to the same stimulus or in different initializations of the same neural architecture. Similar representations occur in settings where data is acquired from multiple modalities (e.g., text and image representations of the same entity) or when observations in a single modality are acquired under different conditions (e.g., multiview learning). The emergence of these similar representations has sparked interest in the fields of Neuroscience, Artificial Intelligence, and Cognitive Science. This workshop aims to get a unified view on this topic and facilitate the exchange of ideas and insights across these fields, focusing on three key points: When: Understanding the patterns by which these similarities emerge in different neural models and developing methods to measure them. Why: Investigating the underlying causes of these similarities in neural representations, considering both artificial and biological models. What for: Exploring and showcasing applications in modular deep learning, including model merging, reuse, stitching, efficient strategies for fine-tuning, and knowledge transfer between models and across modalities. Topics A non-exhaustive list of the preferred topics includes: - Model merging, stitching, and reuse - Representational alignment - Identifiability in neural models - Symmetry and equivariance in NNs - Learning dynamics - Disentangled representations - Multiview representation learning - Representation similarity analysis - Linear mode connectivity - Similarity-based learning - Multimodal learning - Similarity measures in NNs Important Dates - Paper submission deadline: Oct 04, 2023 – Submit on OpenReview <https://openreview.net/group?id=NeurIPS.cc/2023/Workshop/UniReps> - Final decisions to authors: Oct 27, 2023 Tracks Submissions to the workshop are organized in two tracks, both requiring novel and unpublished results: an Extended abstract track, which will address early-stage results, insightful negative findings, opinion pieces, and a Proceedings track, which will address complete papers to be published in a dedicated workshop proceedings volume. Both tracks will be included in the workshop poster session to give an opportunity to authors to present their work, and a subset of the submissions will be selected for a spotlight talk session during the workshop. Paper FormatThe full paper submissions must be at most 9 pages long (excluding references and supplementary materials) and anonymized. We will follow the Neurips general conference submission criteria for papers - for details please see: NeurIPS Call For Papers <https://nips.cc/Conferences/2023/CallForPapers>. As a note, the reviewers will not be required to review the supplementary materials, so ensure your paper is self-contained. For the extended non-archival abstracts please use the same template but limit the submission to 4 pages, excluding references. The submission site will have an option to differentiate full papers and extended abstracts. Please make sure to use the NeurIPS LaTeX template <https://media.neurips.cc/Conferences/NeurIPS2023/Styles/neurips_2023.tex> and style file <https://media.neurips.cc/Conferences/NeurIPS2023/Styles/neurips_2023.sty>.

Sept. 15, 2023

Postdoc on Dravet syndrome modeling (Inria, BCAM, Achucarro)

by desroche

Dear all, We have funds for a two-year postdoc on Dravet syndrome modeling. This is part of an international collaboration between Inria (Bordeaux, Montpellier, Sophia Antipolis, France) and BCAM - the Basque Center for Applied Mathematics (Bilbao, Spain), involving Fabien Campillo, Pierre Del Moral, Mathieu Desroches and Serafim Rodrigues. The postdoc will be based at Inria, in Montpellier. The aim of the project is to develop a multiscale model of Dravet syndrome, from ionic channels of interacting neurons to large neural populations. We will use various modeling frameworks, adapted to the scale, from piecewise-deterministic Markov processes to mean-field formalism. The postdoc will perform a mathematical analysis of the models, extensive numerical simulations as well as data analysis using neural recordings from our experimental partners. Regarding profiles that we are seeking, familiarity of the candidate with mathematical modeling in Neuroscience and Markov processes. Ability and willingness to do programming, as well as analyse experimental data, will also be a strong point to select candidates. Please apply online via the following page: https://jobs.inria.fr/public/classic/en/offres/2023-06688 Best, Mathieu Desroches. --------------------------------------------------------------------- Dr. Mathieu Desroches Research Director (Directeur de Recherche) MathNeuro <https://team.inria.fr/mathneuro/> Project Team Leader Centre Inria d'Université Côte d'Azur, France https://www-sop.inria.fr/members/Mathieu.Desroches/

Sept. 15, 2023

Scientific Computing Associate - Biophysical Modeling - Janelia Farm Research Campus

by Ahmed El Hady

Below an exciting opportunity in Janelia Farm Research Campus to be part of an exciting collaboration if you are into scientific computing, software development and interaction with state of the art biophysics experiments: The Scientific Computing Associate (SCA) <https://www.janelia.org/support-team/scientific-computing-software/scientif…> II position represents an alternative to traditional scientific roles (e.g. postdoc) and provides an ideal environment to establish a career in computational research or software engineering. The position aims at developing qualifications and experience in computational research and professional software engineering in a research environment that enables the candidate to pursue their future career in science or industry. For each project, the SCA will be paired with an experienced software engineer and a member from the specific lab, often the lab head, to quickly learn techniques and about the project itself. The developed software will be openly accessible and the SCA will have the opportunity to become a lead contributor and to potentially publish results. The SCA position is a time-limited appointment for 12 to 24 months, with discretionary renewal for a 12-month term (maximum of 36 months in total). *What We Provide:* * A competitive compensation package, with comprehensive health and welfare benefits. * The opportunity to collaborate with skilled scientists and software engineers and work alongside computational and experimental enthusiasts * The ability to work as an independent scientist * An exciting and inspiring work environment at HHMI Janelia *What You’ll Do:* We are seeking an SCA to join our team at HHMI Janelia to lead a project aimed at /in silico/ biophysical modeling of extracellular ion dynamics in the mammalian brain. Dr. Kayvon Pedram <https://www.pedramlab.com/> will provide mentorship on biochemical aspects of the work; Dr. Ahmed El Hady <https://www.ab.mpg.de/person/111828/2736> will provide mentorship in theoretical neuroscience; and Dr. Stephan Preibisch <https://www.janelia.org/people/stephan-preibisch> and his team will provide mentorship in algorithm development and software engineering. Successful candidates will be interested in exerting intellectual and operational freedom to tackle research objectives at the intersection of these three fields. In brief, neurons convey information through electric pulses, which are generated by rapid ion transport between the cell’s interior and the local extracellular environment. These action potentials propagate from one neuron to the next via chemical synapses, where neurotransmitter-containing vesicles are released into the extracellular space for detection by neighboring neurons. The process of neurotransmitter release itself depends on a rapid, synaptically localized calcium exchange with the extracellular environment. While it is widely understood that transmembrane ion gradients are a crucial aspect of the biophysics that underlies communication within neuronal networks, there is a much more limited understanding of how molecules in the extracellular space, which are heterogenous and actively remodeled throughout the brain, contribute to neuronal communication over a variety of spatial and temporal scales. You will build theoretical frameworks and computational models to explore how extracellular factors, such as ion-ion interactions and mechanical perturbations, influence the diffusion of charged molecules, and subsequently, neuronal excitability. You can expect a close, bidirectional relationship between your theory/modeling efforts and experiments ongoing in the lab and will have the opportunity to test theoretical predictions in the laboratory, if desired. A detailed project description and bibliography will be provided to candidates at the interview stage. *What You Bring:* * M.S. or Ph.D. in Computer Science, Physics, Neuroscience, or related fields (e.g., Biology, Chemistry, Engineering). * Extensive coding experience * Collaborative and collegial attitude toward staff at all levels. For more information and application , please check here: https://hhmi.wd1.myworkdayjobs.com/en-US/External/job/Janelia-Research-Camp…

Sept. 15, 2023

Postdoc in Barcelona

by Quian Quiroga, Rodrigo (Prof.)

We are looking for a postdoc to study single cell recordings in humans, performed in epileptic patients for curative surgery. The position will be in the recently established group of Prof. Quian Quiroga at the Hospital del Mar Research Institute, in Barcelona (https://www.imim.es<https://www.imim.es/>). The project will investigate concept cells (a.k.a. Jennifer Aniston neurons) – that means, neurons in the hippocampus and surrounding areas that selectively fire to specific concepts, like different pictures and the written or spoken name of a particular person (e.g. Quian Quiroga et al, Nature 2005; Quian Quiroga, Cell 2019), which are involved in declarative memory functions. For more details see: https://web.archive.org/web/20220108024112/https://www2.le.ac.uk/centres/cs…<https://web.archive.org/web/20220108024112/https:/www2.le.ac.uk/centres/csn…> The successful candidate will contribute to performing recordings with patients and the analysis / modelling of the data to investigate the role of these neurons in memory. The candidate should have very good quantitative skills (data processing and programing, e.g. in Matlab) and a strong background or interest in neuroscience. Informal enquiries are welcome and should be made to Prof. Rodrigo Quian Quiroga (rquian(a)imim.es) To apply see instructions in this link: https://www.imim.es/ofertes/es_detall-oferta-temporals.html?id=2343 Review of applications will start on the 2nd October 2023, and will continue until the position is filled. Best, Rodrigo Quian Quiroga

Sept. 14, 2023

1st EBRAINS National Node Germany Workshop ***26.09.2023 in Berlin, Germany***

by Frings, Maren

Dear Colleagues, We would like to kindly invite you to participate the 1st EBRAINS National Node Germany Workshop which will take place on September 26, 2023 in Berlin from 09:00-13:30 CET. Guest Speakers: Dr. Seán Froudist-Walsh, University of Bristol Prof. Dr. Thomas Wachtler, Ludwig-Maximilians-University Munich Prof. Dr. Lena Oden, FernUni Hagen & FZ Jülich Prof. Dr. Bryan Strange, Technical University Madrid Dr. Andreas Rowald, Friedrich Alexander University Erlangen-Nürnberg Prof. Dr. Petra Ritter, Charité Universitätsmedizin Berlin Prof. Dr. Thanos Manos, Cergy Paris University For further details and for registration please browse to our <https://flagship.kip.uni-heidelberg.de/jss/HBPm?m=SgD&mI=254> event website. The EBRAINS National Node Germany (NNG) invites to the 1st EBRAINS NNG Workshop as a back-to-back event of the Bernstein Conference 2023 in Berlin, Germany. You will hear about the EBRAINS RI, its usage, an Expert Discussion on Digital tools to bridge the gap between experimental and computational neuroscience and will have the opportunity to network during our NNG lunch. <https://ebrains.eu> EBRAINS is a unique digital Research Infrastructure (RI), created by the EU-funded Human Brain Project. It is an open platform providing an extensive range of data and tools to enhance brain-related research. EBRAINS is a pan-European distributed network of services, that will in the future be organized through National Nodes. The <https://www.ebrains.eu/national-nodes/germany> EBRAINS NNG currently encompasses about 40 universities and research institutions across Germany joining forces to develop a common scientific and technical strategy, addressing the major scientific challenges of our time. The EBRAINS NNG partners offer unique services, including science liaison activities, for basic neuroscience, medical applications, and industry in the fields of: * High-Performance Computing * Neuromorphic Computing * Artificial Intelligence * Simulation * Robotics * Information privacy and security Programme Committee: Nicola Palomero-Gallagher, Petra Ritter, Fabrice Morin, Francesca Cavallaro, Björn Kindler, Sandra Diaz, Maren Frings. In case of further questions please dont hesitate to contact ebrains-nng(a)fz-juelich.de <mailto:ebrains-nng@fz-juelich.de> Kind regards Maren Frings on behalf of the Programme Committee Dr. Maren Frings Project Manager, EBRAINS National Node Germany Jülich Supercomputing Centre Institute for Advanced Simulation Tel +49 2461 61-6431 Fax +49 2461 61-6656 <http://www.fz-juelich.de/ias/jsc> www.fz-juelich.de/ias/jsc ------------------------------------------------------------------- Forschungszentrum Jülich GmbH 52425 Jülich Sitz der Gesellschaft: Jülich Eingetragen im Handelsregister des Amtsgerichts Düren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Stefan Müller Geschäftsführung: Prof. Dr.-Ing. Wolfgang Marquardt (Vorsitzender), Karsten Beneke (stellv. Vorsitzender), Dr. Ir. Pieter Jansens, Prof. Dr. Astrid Lambrecht, Prof. Dr. Frauke Melchior -------------------------------------------------------------------

Sept. 14, 2023

[jobs] 3.5-year PhD Scholarship in Human-like performance in neuromorphic robots

by Di Nuovo, Alessandro

All applications must be submitted using the online application form<https://www.findaphd.com/common/clickCount.aspx?theid=160616&type=184&DID=6…>. To apply, click here<https://www.findaphd.com/common/clickCount.aspx?theid=160616&type=184&DID=6…> For information on how to apply please visit https://www.shu.ac.uk/research/degrees<https://www.findaphd.com/common/clickCount.aspx?theid=160616&type=184&DID=6…> About the Project This scholarship is to support the Horizon Europe project PRIMI: Performance in Human Robot Interaction via Mental Imagery, led by Professor Alessandro Di Nuovo (scientific coordinator). The project aims to create the next-gen humanoid robots with efficient computation, high cognition, and autonomy, by synergistically combining interdisciplinary research development in neurophysiology, psychology, machine intelligence, cognitive mechatronics, neuromorphic engineering, and humanoid robotics. The PRIMI project seeks to create more capable interactive robots with advanced abilities, able to provide innovative and personalised services. Prototypes will be used in stroke rehabilitation studies. You will join the Smart Interactive Technologies (SIT) research laboratory; a vibrant interdisciplinary group, led by Prof. Alessandro Di Nuovo, that conducts world-leading research on Artificial Intelligence and Robotics. The group is currently running several research projects worth over £2.5 million funding from the European Commission and UKRI. This PhD project will focus on machine intelligence techniques and neuromorphic computing technologies to create active inference models for interactive learning in robots with human-like performance. Background Humans can learn faster with less data by reducing surprise or uncertainty by making predictions based on internal models. Indeed, neurophysiology and developmental psychology increasingly highlight the embodied nature of intelligence, which is shaped the experiences acquired through the body, such as manipulatives, gestures, and movements. To overcome the current limitations, the research methodology will adopt the developmental neuromorphic approach with cognitive agents that are embodied in humanoid robotic platforms. Developmental robotics fundamentally differs from traditional machine learning as it targets task-independent self-determined learning via interaction with the environment rather than task-specific inference over selected, human-edited sensory data. It also differs from traditional cognitive robotics because it focuses on the processes that allow the formation of cognitive capabilities rather than these capabilities themselves. Neuromorphic computing investigates large-scale processing systems that support natural neuronal computations through spike-driven communication to imitate the efficient neuro-synaptic framework of the physical brain. Compared to traditional approaches, key advantages of neuromorphic computing are energy efficiency, execution speed and robustness against local failures. Eligibility Candidates should have (or expect to obtain before the start of the PhD) a minimum of an upper second-class honours degree (2.1) or equivalent in Computer Science, Neuroscience, or a closely related subject. To be eligible for a waiver of the international fees, candidates should have a strong Master's degree and/or scientific publications on the subject of the research project. For further details on entry requirements, please click here<https://www.findaphd.com/common/clickCount.aspx?theid=160616&type=184&DID=6…> How to apply All applications must be submitted using the online application form<https://www.findaphd.com/common/clickCount.aspx?theid=160616&type=184&DID=6…>. To apply, click here<https://www.findaphd.com/common/clickCount.aspx?theid=160616&type=184&DID=6…>. We strongly recommend you contact the lead academic, Prof. Alessandro Di Nuovo, a.dinuovo(a)shu.ac.uk<javascript:void(0)>, to discuss your application. Start date for studentship: February 2024 Interviews are scheduled for: TBC

Sept. 14, 2023

looking for a postdoc on modeling / optimization of brain stimulation

by Dana Brooks

Postdoctoral Research Fellow at UMass Boston A postdoctoral fellow position is available in the Brain Stimulation & Simulation Lab <https://www1.coe.neu.edu/%7Erampersad/index.html>, directed by Dr. Sumientra Rampersad, in the Department of Physics at the University of Massachusetts Boston. Our lab focuses on investigating electromagnetic brain stimulation through computational methods and experiments with healthy volunteers. This position is funded by a newly awarded 5-year NIH R01 <https://reporter.nih.gov/project-details/10719222> grant with the goal to investigate a novel form of brain stimulation called transcranial temporal interference stimulation (TIS) and to optimize and translate it into an effective and efficient neuromodulation method for academic research and clinical practice. The fellow will develop novel optimization methods for high-density TIS and supervise a PhD student who will conduct simulations and optimizations using finite element modeling. The goal is to provide noninvasive and spatially specific treatment options to patients with brain disorders resistant to existing approaches. You will join a multidisciplinary team with expertise in computational modeling and optimization, human and primate electrophysiology, cellular and systems neuroscience, and biomedical engineering. You will also have the opportunity to work on other cutting-edge projects involving several brain stimulation methods including tCS, TMS, ECoG, sEEG and TTF (see lab website <https://www1.coe.neu.edu/%7Erampersad/index.html> for examples). Our collaborators at Northeastern University, the University of Utah, Harvard University, MGH, and the University of Washington, provide us access to specialized software and unique clinical data. The fellow will be mentored by Dr. Rampersad (UMass Boston) and Dr. Dana Brooks (Northeastern). This is an outstanding career development opportunity to work with leaders in the field of brain stimulation with an exceptional record of collaboration and mentoring. Required qualifications include a PhD in physics, math, electrical, biomedical engineering, or equivalent, expertise in either brain stimulation modeling or computational optimization methods (preferred both), a track record of conference presentations and peer-reviewed publications, strong verbal and written communication skills, and proficiency in Matlab or Python. This is a one-year appointment with the possibility of extension provided satisfactory progress is made. To apply, send a cover letter and CV to Dr. Rampersad (sumientra.rampersad(a)umb.edu) with the subject “TIS postdoc”. Please describe in detail your experience with optimization, brain stimulation, FEM, coding, project management, and mentoring students.

Sept. 14, 2023

Faculty postion at Harvard bridging computational neuroscience and AI

by Blum, Kenneth I.

The Center for Brain Science (CBS) and Kempner Institute for the Study of Natural and Artificial Intelligence at Harvard University seek a tenure-track faculty member working across the fields of computational neuroscience and a machine learning approach to AI. Please forward this information to any interested candidates. Applications should be submitted to this site: https://academicpositions.harvard.edu/postings/12751. ***** HARVARD UNIVERSITY CENTER FOR BRAIN SCIENCE and KEMPNER INSTITUTE FACULTY POSITION The Center for Brain Science (CBS) and Kempner Institute for the Study of Natural and Artificial Intelligence at Harvard University seek a tenure-track faculty member to lead an innovative research program working across the fields of Computational Neuroscience and Machine Learning to discover how brain computation can benefit artificial systems and how principles of computation and learning in artificial systems can be used to understand the brain. Current faculty use a variety of approaches to learn how brains compute and govern cognition and behavior. The successful candidate will be appointed an Institute Investigator within the Kempner Institute and will hold an academic appointment in an appropriate department in the life or physical sciences in the Faculty of Arts and Sciences at Harvard University. A full list of potential departments can be found here: science.fas.harvard.edu/pages/about<https://science.fas.harvard.edu/pages/about>. CBS (cbs.fas.harvard.edu<https://cbs.fas.harvard.edu/>) fosters interactions across disciplinary boundaries—faculty from several academic departments have neighboring labs and share common research facilities and meeting space; its connections also reach out across the University. The Kempner Institute (harvard.edu/kempner-institute<https://www.harvard.edu/kempner-institute/>) is building a community of scholars, who work across boundaries and fields to advance our understanding of intelligence, broadly speaking. Investigators will join a dynamic community of researchers to study intelligence from biological, cognitive, engineering, and computational perspectives. A doctoral degree in the life and physical sciences, or a related discipline is required by the time the appointment begins. Candidates should have demonstrated excellence in both research and teaching. A strong doctoral record is required and postdoctoral experience preferred. Teaching will include offerings at both undergraduate and graduate levels. To apply, please use this link to submit a cover letter; curriculum vitae; three-page research statement; statement of teaching and advising philosophy; statement describing efforts to encourage diversity, inclusion, and belonging, including past, current, and anticipated future contributions in these areas; and up to three publications: https://academicpositions.harvard.edu/postings/12751. Please also submit contact information, including email addresses, for 3-5 people who will be asked by a system-generated email to upload a letter of recommendation once the candidate’s application has been submitted. Three letters of recommendation are required, and the application is considered complete only when at least three letters have been received. At least one letter must come from someone who has not served as the candidate’s undergraduate, graduate, or postdoctoral advisor. We will begin considering applications as they are received, but all materials, including letters of reference, should be submitted by October 15, 2023. Note that there are three additional faculty searches ongoing currently with the Kempner Institute at Harvard University. One is in partnership with Psychology, another with Computer Science, and a third with Applied Mathematics. If applying to more than one, please read the search criteria carefully. The health of our workforce is a priority for Harvard University. With that in mind, we strongly encourage all employees to be up to date on CDC-recommended vaccines. We strongly welcome applications from persons from underrepresented groups. Harvard University is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, sex, gender identity, sexual orientation, religion, creed, national origin, ancestry, age, protected veteran status, disability, genetic information, military service, pregnancy and pregnancy-related conditions, or other protected status.

Sept. 13, 2023