- Comp-neuro - lists.cnsorg.org

The Gatsby Unit PhD programme

by Maneesh Sahani

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

Nov. 2, 2021

Master in Brain and Cognition, Barcelona

by Ruben Moreno Bote

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>

Nov. 2, 2021

job: machine learning research scientist at NIMH

by Francisco Pereira

## 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!

Nov. 2, 2021

postdoc position on brain-machine interfaces at NYU & UO

by Luca Mazzucato

The Kiani (NYU) and Mazzucato (UO) labs are looking for a computational neuroscience postdoc to lead a project on closed-loop behavioral control in primates using a brain-machine interface. The candidate will develop a new theoretical framework to infer causal interactions from sparse sampling of large neural ensembles and deploy this method in the prefrontal cortex of behaving primates. The goal of this project is to innovate a technique for targeted manipulation of the prefrontal circuit and alter the monkey’s cognitive behavior in real-time, a key step toward advanced brain-machine interfaces and novel enhancing or therapeutic interventions in the human brain. The theory position will be co-supervised between the labs of Roozbeh Kiani at New York University and Luca Mazzucato at University of Oregon. The postdoc will be part of the vibrant neuroscience and machine learning communities at the Center for Neural Sciences (NYU) and at the Institute of Neuroscience (UO). The postdoc will be a member of the NSF-funded Accelnet consortium "International network for brain-inspired computation," fostering international collaborations between a large network of computational neuroscience/AI labs. Successful candidates will have a PhD in Physics, Neuroscience, Mathematics, Computer Science, Engineering, Statistics or a related discipline and, preferably, working experience in theoretical neuroscience and deep learning. Our labs strongly advocate for inclusivity in science and we encourage applications from underrepresented groups. For informal inquiries about the position please contact Roozbeh Kiani or Luca Mazzucato. Application reviews will start on Nov. 15 and will continue until the position is filled. Roozbeh Kiani & Luca Mazzucato

Nov. 1, 2021

Modellers Workshop for the Brain Dynamics Toolbox

by Stewart Heitmann

Modeller’s Workshop for the Brain Dynamics Toolbox Online Course. Enrolments open 1-20 Nov 2021. This is a practical, self-paced course for researchers and students who wish to build their own dynamical models using the Brain Dynamics Toolbox (bdtoolbox.org<http://bdtoolbox.org>). Participants learn the art of programming differential equations to simulate neuronal dynamics. Topics include programming Ordinary Differential Equations, Partial Differential Equations, Delay Differential Equations, Stochastic Differential Equations, Auxiliary Plot Functions and command-line tools. Example code is provided in all cases. Study time is 8 hours. Course Website https://bdtoolbox.org/p/modellers-workshop/ Important Dates Early-bird enrolments ($125) close Saturday 6th Nov, 2021. Late enrolments ($150) close Saturday 20th Nov, 2021. Stewart Heitmann | Computational Scientist Victor Chang Cardiac Research Institute | Lowy Packer Building | 405 Liverpool St, Darlinghurst NSW 2010 Australia E: s.heitmann(a)victorchang.edu.au<mailto:s.heitmann@victorchang.edu.au> | @VictorChangInst Disclaimer The information contained in this communication from the sender is confidential. It is intended solely for use by the recipient and others authorized to receive it. If you are not the recipient, you are hereby notified that any disclosure, copying, distribution or taking action in relation of the contents of this information is strictly prohibited and may be unlawful. This email has been scanned for viruses and malware, and may have been automatically archived by Mimecast Ltd, an innovator in Software as a Service (SaaS) for business. Providing a safer and more useful place for your human generated data. Specializing in; Security, archiving and compliance. To find out more visit the Mimecast website.

Oct. 31, 2021

Postdoc in Brain Computer Interfaces, Melbourne, Australia

by David Grayden

We are recruiting a Postdoctoral Research Fellow to join the Department of Biomedical Engineering, University of Melbourne, Australia as part of the Australian Research Council Training Centre in Cognitive Computing for Medical Technologies. The Training Centre aims to create a workforce that is expert in developing, applying and interrogating artificial intelligence technologies in data-intensive medical contexts. Research Fellow in Brain Computer Interfaces will aim to develop a brain-computer interface (BCI) that can be used to control commercially available augmentative devices for people with speech, vision or motor disorders. Details: https://jobs.unimelb.edu.au/caw/en/job/906909/ Applications close: 11:55 pm 19 November 2021 Australian Eastern Daylight Time (UTC/GMT+11 hours) Regards, David Professor David B. Grayden Clifford Chair of Neural Engineering Director, Medical Technologies Platform Dept of Biomedical Engineering Faculty of Engineering and Information Technology The University of Melbourne, Victoria 3010 Australia https://biomedical.eng.unimelb.edu.au/ | https://www.linkedin.com/in/dgrayden This email and any attachments may contain personal information or information that is otherwise confidential or the subject of copyright. Any use, disclosure or copying of any part of it is prohibited. The University does not warrant that this email or any attachments are free from viruses or defects. Please check any attachments for viruses and defects before opening them. If this email is received in error please delete it and notify us by return email.

Oct. 29, 2021

Job Posting: MindCORE Postdoctoral Research Fellowships at UPenn

by Calvert, Heather J

MindCORE Postdoctoral Research Fellowships MindCORE seeks to recruit outstanding postdoctoral researchers for our Research Fellowship for Postdoctoral Scholars. Housed within the School of Arts and Sciences of the University of Pennsylvania, MindCORE (https://mindcore.sas.upenn.edu/) is an interdisciplinary effort to understand human intelligence and behavior. Designed for individuals who have recently obtained a PhD degree in psychology, linguistics, neuroscience, philosophy, computer science or other cognitive science discipline, the MindCORE Fellowship is a springboard for young researchers as they establish their own research program. Fellows are also encouraged to pursue collaborative research with faculty working across disciplines at Penn. Benefits Fellows receive a competitive salary, relocation allowance, health insurance, plus a modest research budget of $20,000. Fellows also benefit from access to the greater community of academics including visiting scholars plus leading research facilities equipped with cutting-edge instrumentation all on an urban campus in a vibrant city. Fellows are invited to join regular working group meetings within their field plus career development workshops aimed at young researchers, and will be provided with a mentoring committee. Funding is provided in one-year terms renewable for up to three years. Eligibility & Application We are accepting applications for 2022-2023 until January 10, 2022. Applicants must have formally completed all requirements of the PhD degree and provide a copy of their diploma at the time of appointment (typically July 1, 2022 - Jan 15, 2023). Candidates must submit a research statement that identifies at least three MindCORE faculty (https://mindcore.sas.upenn.edu/people/faculty-and-associates/) at Penn with whom the applicant could potentially collaborate; along with a CV, and contact information for two referees. Complete applications should be submitted along with some basic information using a form available on the website: https://mindcore.sas.upenn.edu/post-doctoral-research-fellowship/. Selection All eligible and complete applications will be evaluated by the Selection Committee after January 10. Applications are judged on the following criteria: Scientific excellence Scientific match and interdisciplinarity Career potential MindCORE seeks to award ~2 post-doctoral Fellowships per year. Positions may start as early as July 1, 2022. Questions? Contact pennmindcore(a)sas.upenn.edu<mailto:pennmindcore@sas.upenn.edu>

Oct. 26, 2021

Postdoc in computational cognitive neuroscience with human neurons in Utah

by ELLIOT H SMITH

Two NIH-funded (5 years) postdoctoral research scientist positions are available in Human Neuronal Computation Laboratory in the Neurosurgery Department at the University of Utah. We are seeking applicants with computational skills (signal processing, data mining, statistical modeling) to study neural representations of abstract space, and distributional reinforcement learning in human neuron activity recorded from epilepsy patients. Please send an email and CV if interested. Thanks, Elliot _____________________________ Elliot H Smith, PhD (he/him) Assistant Professor Department of Neurosurgery University of Utah 175 N Medical Drive #5 Salt Lake, City, UT 84132 e.h.smith(a)utah.edu<mailto:e.h.smith@utah.edu> +1-206-349-1249

Oct. 26, 2021

NEXT WEEK: New Approaches to 3D Vision, 1st-4th Nov 2021, Royal Society online meeting

by Linton, Paul

NEXT WEEK: NEW APPROACHES TO 3D VISION, 1st-4th November 2021, hosted by the Royal Society This Royal Society online meeting brings together researchers from computer vision, animal vision, and human vision to explore recent developments in 3D vision. Speakers reflect both academia and industry, with representatives from DeepMind, Facebook Reality Labs, Google, and Microsoft Research. Date/Time: 1st-4th November 2021, 3-6pm (3-6:30pm on the 4th), UK Time Please note that the USA/UK time difference is 1hr less than usual Website: https://royalsociety.org/science-events-and-lectures/2021/11/3d-vision/ Registration (Free): https://www.eventbrite.co.uk/e/new-approaches-to-3d-vision-registration-165… DAY ONE (1st Nov) - Seeing Beyond SLAM Chair: Andrew Fitzgibbon (Microsoft) Session One: Neural Scene Representation SM Ali Eslami (DeepMind): “Neural priors, neural encoders and neural renderers” Ida Momennejad (Microsoft Research): “Multi-scale predictive representations and human-like RL” Session Two: Perception-Action Loop Sergey Levine (UC Berkeley and Google): “Generalization in data-driven control” Andrew Glennerster (University of Reading): “Understanding 3D vision as a policy network” DAY TWO (2nd Nov) - Animals in Action Chair: Matteo Carandini (University College London) Session One: Locating Prey and Rewards Jenny Read (Newcastle University): “Stupid stereoscopic algorithms that still work” Aman Saleem (University College London): “Visual processing in the brain during navigation” Session Two: Navigation in 3D Space Kate Jeffery (University College London): “The cognitive map of 3D space: not as metric as we thought?” Gily Ginosar (Weizmann Institute of Science): “Locally ordered representation of 3D space in the entorhinal cortex” DAY THREE (3rd Nov) - Experiencing Space Chair: Mar Gonzalez-Franco (Microsoft Research) Session One: Theories of Visual Space Dhanraj Vishwanath (University of St Andrews): “Tripartite encoding of visual 3D space” Paul Linton (City, University of London): “New approaches to visual scale and visual shape” Session Two: Challenges for Virtual Reality Sarah Creem-Regehr (University of Utah): “Perception and Action in Virtual and Augmented Reality” Douglas Lanman (Facebook Reality Labs): “Engineering challenges for realistic displays” DAY FOUR (4th Nov) - Grasping the World Chair: Jody Culham (Western University) Session One: One Visual Stream or Two? Fulvio Domini (Brown University): “A novel non-probabilistic model of 3D cue integration explains both perception and action” Irene Sperandio (University of Trento): “Dissociations between perception and action in size-distance scaling” Session Two: 3D Space and Visual Impairment Ione Fine (University of Washington): “Do you hear what I see? How do early blind individuals experience object motion?” Ewa Niechwiej-Szwedo (University of Waterloo): “The role of binocular vision in the development of visuomotor control and performance of fine motor skills” Session Three: Panel Discussion Andrew Fitzgibbon (Microsoft), Matteo Carandini (University College London), Mar Gonzalez-Franco (Microsoft Research), and Jody Culham (Western University), share their thoughts on the future of 3D vision with an interactive Question and Answer session. Organisers: Michael Morgan FRS (City, University of London), Paul Linton (City, University of London), Jenny Read (Newcastle University), Dhanraj Vishwanath (University of St Andrews), Sarah Creem-Regehr (University of Utah), Fulvio Domini (Brown University)

Oct. 26, 2021

WWNeuRise series on the neuroscience of navigation

by William Podlaski

WorldWideNeuRise will host several online talks throughout November-December on the topic of the neuroscience of navigation from the following speakers (titles TBA): Wednesday, 3 November, 5pm CET Erik Hermansen (Dunn Lab, NTNU) Sarthak Chandra (Fiete Lab, MIT) Wednesday, 17 November, 5pm CET Salman Qasim (Gu Lab, Mount Sinai) Jacob Bellmund (Doeller Lab, MPI CBS / Kavli Institute) Wednesday, 1 December, 5pm CET Hannah Payne (Aronov Lab, Columbia University) Nick Robinson (Hausser Lab, UCL) Wednesday, 8 December 5pm CET Philip Shamash (Branco Lab, UCL) Anna Gillespie (Frank Lab, UCSF) For more information, please visit our website (https://neurise.github.io/) find us on WorldWideNeuro (https://www.world-wide.org/Neuro/WWNeuRise/) or follow us on Twitter (https://twitter.com/WWNeuRise) We are always searching for PhD students and postdocs to give talks in our upcoming seminars on any topic in systems neuroscience. On our website ( https://neurise.github.io/) you can find an application form to directly apply, as well as a recommendation form, where you can suggest individuals from your lab, institute, or otherwise who you think might have an interesting story to tell! We are looking forward to seeing you at our upcoming seminars! The organising committee, Ellen Boven (Apps lab, University of Bristol) Christina Buetfering (Häusser lab, University College London) Wesley Clawson (Levin lab, Tufts University) Lucie Descamps (Kentros lab, Norwegian University of Science and Technology) Gily Ginosar (Ulanovsky lab, Weizmann Institute) Loreen Hertäg (Clopath lab, Imperial College London) Joram Keijser (Sprekeler lab, TU Berlin) Bill Podlaski (Machens lab, Champalimaud Research)

Oct. 25, 2021