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Call for community review: The Essential Metadata for 3D BRAIN Microscopy metadata standards (3D-MMS)
by INCF Dec. 7, 2022

Dec. 7, 2022

*INCF seeks community feedback on the 3D Microscopy Metadata Standard (3D-MMS)* Recent advances in fluorescence microscopy techniques and tissue clearing, labeling, and staining provide unprecedented opportunities to investigate brain structure and function, and to catalog brain cell types and define their location, morphology, and connectivity in a native context. It is essential to establish and adopt standards for annotating, reporting, and formatting imaging datasets so that other researchers can understand, reuse, and integrate microscopy data. The Essential Metadata for 3D BRAIN Microscopy metadata standards (3D-MMS) were built on existing efforts and developed with input from the brain microscopy community to promote adoption. The metadata standards include 91 fields organized into seven categories: Contributors, Funders, Publication, Instrument, Dataset, Specimen, and Image. Each metadata field is specified by a name, definition, a list of allowable values, whether it is required, and the number of times it can be repeated for a dataset. These metadata standards were developed by the BRAIN 3D Microscopy Working Group, and are being implemented within the Brain Image Library, the designated repository to accept and make microscopy data publicly available for investigators funded by the US BRAIN Initiative. Comments on this standard are open until February 3, 2023. Add your comments here: bit.ly/ComRevDec22 Why is it important to comment? Community feedback on standards & best practices helps us identify how standards can be improved to be as interoperable as possible with the systems, software, and resources that are currently being used in the field. Find out how to submit your feedback: bit.ly/INCFreview You can comment to express your support, help us identify potential weaknesses, or highlight possibilities for making the standard better or more useful. We value all feedback! Read the INCF criteria for endorsement: bit.ly/INCFreviewcriteria Community review report: bit.ly/ComRevDec22 3D-MMS in the INCF SBP catalog: bit.ly/INCFsbpBRAIN Project page: bit.ly/DORyProject 3D-MMS on Github: bit.ly/3DMMSonGH 3D-MM in Nature: go.nature.com/3VWdcWX Thanks for your help! /The INCF Team

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Postdoc on Brain network mechanisms underlying spatial cognition
by Peter Dayan Dec. 7, 2022

Dec. 7, 2022

Postdoc position (m/w/d): Brain network mechanisms underlying spatial cognition A postdoc position is available at the Department of Computational Neuroscience at the Max Planck Institute for Biological Cybernetics to work with Dr. Oxana Eschenko on brain network mechanisms underlying spatial cognition. This project is a follow up study (Yang; https://www.jneurosci.org/content/jneuro/39/3/434.full.pdf; Mei; http://learnmem.cshlp.org/content/25/3/129) aiming at understanding the role of two thalamic nuclei – the nucleus reuniens and mediodorsal nucleus - within a large-scale brain network underlying spatial cognition. The involvement of both thalamic nuclei in spatial cognition can be inferred from anatomical connectivity and neuropharmacology, while neurophysiological mechanisms of the spatial network dynamics remain poorly understood. We hypothesize that a functional coupling exists between the associative thalamic nuclei, the hippocampus, and the prefrontal cortex and that this coupling enables successful spatial navigation and retrieval of spatial memory. To test this hypothesis, we recorded multi-site neural activity while rats learned a complex maze task, and plan to relate model-agnostic and model-dependent behavioral variables reflecting learning and decision-making to aspects of the extracellular neural signals, including spectral decomposition, coherence, cross-frequency and phase-amplitude analysis. Candidates should have strong computational and data science skills and proven experience in the analysis of behavior and neural signals. Proficiency in English is essential. The position is available from March 1, 2023 and will be for one year in the first instance, subject to a probationary period. An extension may be possible depending on performance. Remuneration is based on qualifications and professional experience in accordance with the collective agreement for the public service (TVöD Bund) plus various social benefits and additional pension provision. The Max Planck Society is an equal opportunity employer: Handicapped individuals are strongly encouraged to apply, and so are women in areas in which they are underrepresented. The Max Planck Society strives for gender and diversity equality. We welcome applications from all backgrounds. Please contact Dr. Eschenko (e-mail: oxana.eschenko(a)tue.mpg.de) with any enquiries. Application deadline is January 31, 2023. Please upload your application documents electronically to our job portal by Jan 31, 2023 using the following link: https://jobs.tue.mpg.de/jobs/191

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Postdoc position in deep learning, closed loop methods, and explainable ML at Cold Spring Harbor Laboratory
by Benjamin Cowley Dec. 6, 2022

Dec. 6, 2022

A postdoctoral position in computational neuroscience /machine learning is available in Dr. Benjamin Cowley’s research group at Cold Spring Harbor Laboratory, NY. We are looking for a computational postdoc broadly interested in using machine learning approaches to answer scientific questions about the brain. We focus on designing *closed-loop methods for systems neuroscience* as well as building *explainable computational models of neural responses and behavior*. An important component of our work is to build tight-knit collaborations with experimental neuroscientists—collecting data and building models in tandem. A long-term goal is to identify and understand the step-by-step computations in the brain. For more information, see cowleygroup.cshl.edu Position Requirements Qualifications: PhD in machine learning, computer science, statistics, engineering, neuroscience, or related field; strong programming skills, publications in machine learning conferences or neuroscience journals, and experience or interest in neuroscience and collaborating with experimentalists. Familiarity with deep learning is recommended but not needed. To apply: Interested candidates should Please submit a CV, a short description of how our research interests overlap, and contact information for two references to: cowley(a)cshl.edu. In addition, please apply via the CSHL careers website at: https://cshl.peopleadmin.com/postings/20312 Position ID 03327-R. Candidates from non-traditional and/or underrepresented backgrounds, broadly defined, are strongly encouraged to apply. Environment Cold Spring Harbor Laboratory is a world-renowned biomedical research institution in New York. It has shaped contemporary biomedical research and is the home of eight Nobel Prize laureates. Cold Spring Harbor Laboratory provides a highly dynamic and interactive research environment and also a unique opportunity of timely exposure to advances in various biomedical research fields and of interaction with a broad range of researchers from all over the world through its renowned Meetings and Courses program. We believe that science is for everyone. We have had researchers with a variety of backgrounds and believe in the importance of diversity, equity, and inclusion. Compensation and Benefits Our employees are compensated from a total rewards perspective in many ways for their contributions to our mission, including competitive pay, exceptional health benefits, retirement plans, paid time off, and a range of recognition and wellness programs. Visit our CSHL Benefits & Postdoctoral Landing sites to learn more.

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Funded PhD position available in Cellular Modelling
by b.flanagan＠ulster.ac.uk Dec. 5, 2022

Dec. 5, 2022

The Intelligent Systems Research Centre at Ulster University is advertising a funded PhD position for a project titled “Computational Biophysical Modelling of Motor Neuron Disease.” Within this PhD, the candidate will explore several different disciplines including neuroscience, physics, and cell biology to develop a computational biophysical model which will help our understanding of the pathway to MN death in ALS. The candidate will consider the environment of the MN neurons, including glutamate pathways, surrounding astrocytes and the movement of ions, integral to proper neuronal function. The candidate will work closely with experimental neuroscientists to validate their model in vitro, to help further our understanding of the disease and offer insights into treatment development. More details about this position are available at https://www.ulster.ac.uk/doctoralcollege/find-a-phd/1455693. The PhD candidate will be based at the Derry campus of Ulster University, rated in the UK’s Top Ten Research Schools. Derry is located on the banks of the River Foyle in the north-west of Northern Ireland, perfectly positioned between the dramatic scenery of the Wild Atlantic Way and the Causeway Coast. It is a vibrant city seeped in history and culture, and its multitude of family-friendly activities makes Derry a great place to live. For more information, visit https://www.visitderry.com/ Essential criteria: Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study. We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction. In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications. Experience using research methods or other approaches relevant to the subject domain. A comprehensive and articulate personal statement. Desirable Criteria If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview. First Class Honours (1st) Degree Masters at 70% For VCRS Awards, Masters at 75% Experience using research methods or other approaches relevant to the subject domain Work experience relevant to the proposed project Publications - peer-reviewed Experience of presentation of research findings Please contact Bronac (b.flanagan(a)ulster.ac.uk) if you are interested or have questions. --

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My Seizure Gauge Seizure Forecasting Challenge
by Levin Kuhlmann Dec. 4, 2022

Dec. 4, 2022

The 'My Seizure Gauge Seizure Forecasting Challenge' is now open from Dec 1 2022 until March 1 2023. The contest is hosted on Eval.ai and has a total prize pool of $USD 16,000. The goal is to develop seizure forecasting algorithms using wearables data. More details are available at the following link https://eval.ai/web/challenges/challenge-page/1693/overview The contest is supported by the Epilepsy Foundation of America, Seer Medical, The Mayo Clinic, Kings College London, The University of Freiburg and Monash University. -- Cheers, Levin Kuhlmann, PhD Senior Lecturer of Data Science, AI and Digital Health Director of Master of AI Faculty of Information Technology Monash University Rm 2.73, Woodside Building, Clayton Campus email: levin.kuhlmann(a)monash.edu phone: +61412 552283 web: https://research.monash.edu/en/persons/levin-kuhlmann

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Postdoc in computational neuroscience at NYU
by Cristina Savin Dec. 2, 2022

Dec. 2, 2022

Applications are invited for a postdoctoral scholar position in the Savin and Angelaki group in the Centre for Neural Science at NYU. The position is funded by a new NIH grant, and focuses on elucidating the mechanisms of spatial navigation using multi-area recordings in freely moving monkeys in the context of foraging tasks. Aspects of this problem include determining the mechanisms representing and updating beliefs about location of self and targets, through the lens of interaction between multiple cortical areas. A significant component of the work focuses on developing new statistical data analysis tools for understanding inter-area communication in the context of naturalistic behavior. This is a joint endeavor across the two lab, with weekly joint meetings and regular group interactions. More broadly, the postdoc will be part of a large and intellectually vibrant community of researchers from the Center for Neuroscience and the Centre for Data Science at NYU. The initial appointment is one year with the expectation of extension contingent on satisfactory progress. The successful applicant will have a degree in computational neuroscience or machine learning, excellent coding skills (python) and a track record of successful research. Prior experience in neural data analysis, probabilistic machine learning, or open software development are particularly appreciated. Prior experience in neuroscience is welcome, but not strictly required. Finally, since this is a highly interdisciplinary and collaborative project, good communication skills are important. Please submit your application to csavin(a)nyu.edu <mailto:csavin@nyu.edu>, including - CV - a statement of research interests - contact details of three people that are familiar with your work We will be evaluating the applications on a rolling basis, starting from Dec 15, 2022, until the position is filled. Cristina Savin Assist.Prof. Neural Science and Data Science New York University

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Fwd: Postdoctoral position in neural coding, UKE, Hamburg (Germany)
by Stefano Panzeri Dec. 2, 2022

Dec. 2, 2022

I am seeking candidates for a fully funded postdoctoral position in computational neuroscience at the University Medical Center Hamburg-Eppendorf (UKE). The successful candidate will conduct research in my computational laboratory (Department of Excellence for Neural Information Processing) at UKE ( https://www.uke.de/english/departments-institutes/institutes/department-of-…) in collaboration with my lab’s experimental collaborators, including prominently Prof. Christopher Harvey at Harvard Medical School, Prof. Tommaso Fellin at IIT Italy, and Prof. Mriganka Sur at MIT. We will investigate, by developing and using advanced data analysis methods and biophysically plausible neural network models, how populations of neurons (and of glia) in the brain encode information and use it to produce appropriate behaviors. We are particularly interested in discovering how correlations between neurons shape the encoding and transmission of information across areas of the cerebral cortex, and in understanding the theoretical principles of how to combine measures and perturbations of neural activity to probe causally the contributions of interactions between neurons to brain function. Our laboratory offers a wide range of interdisciplinary expertise in computational neuroscience, including both advanced neural analysis techniques and neural network modeling. The laboratory also offers a thriving, ambitious and well-funded research environment (including receiving funding from the NIH Brain Initiative, Simons Foundation, the European Union). This gives successful candidates ample opportunities for advanced training and personal scientific growth. We seek candidates holding a PhD in a numerate or neuroscientific discipline, with a solid computational background and a keen interest in neuroscience. They must be highly motivated and creative individuals who want to work in a dynamic, multi-disciplinary research environment and be willing to interact with both experimental and theoretical neuroscientists. The job is available starting immediately and applications will be considered as soon as they are received and until the position is filled. Funding is available for several years and a minimum commitment of two years is expected by interested candidates. Interested applicants are strongly encouraged to email me (s.panzeri(a)uke.de or stefano.panzeri(a)gmail.com) as soon as possible, to inform me of the interest for the position and initiate a discussion about research projects. I suggest interested candidates to attach a CV when inquiring by email. For recent publications from my lab relevant to this project, see: Panzeri S, et al (2022) The structures and functions of correlations in neural population codes. *Nature Reviews Neuroscience* 23: 551-567 Koren V., Panzeri S (2022) Biologically plausible solutions for spiking networks with efficient coding. *NeurIPS 2022,* in press, arXiv:2210.07069 Curreli S, et al (2022) Complementary encoding of spatial information in hippocampal astrocites. *PLoS Biology* 20(3): e3001530. Valente, M. et al (2021), Correlations enhance the behavioral readout of neural population activity in association cortex. *Nature Neuroscience*, 24, 975–986 Chong, E. et al (2020) Manipulating synthetic optogenetic odors reveals the coding logic of olfactory perception. *Science* 368, 1329. Runyan C. A., et al (2017) Distinct timescales of population coding across cortex, *Nature*: 548: 92-96. Panzeri S., et al (2017) Cracking the neural code for sensory perception by combining statistics, intervention and behaviour. *Neuron* 93: 491-507 Pica, G. et al (2017) Quantifying how much sensory information in a neural code is relevant for behavior, *Neural Information Processing Systems (NeurIPS 2017)* Thanks Stefano Panzeri

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Post-doc and graduate positions in DeAngelis lab, with Moreno-Bote and Drugowitsch Labs
by Ruben Moreno Bote Dec. 2, 2022

Dec. 2, 2022

Postdoctoral and PhD positions in systems neuroscience, DeAngelis Lab, University of Rochester, in collaboration with Moreno-Bote and Drugowitsch Labs. A postdoctoral position and a graduate student assistantship in Systems Neuroscience are available at the University of Rochester, in the laboratory of Dr. Greg DeAngelis. The positions are part of a recently funded NIH project on the neural mechanisms of visually-guided navigation in virtual reality. The project is a collaboration with the laboratories of Dr. Ruben Moreno-Bote (UPF, Barcelona) and Dr. Jan Drugowitsch (Harvard Medical School, Boston). A 1-month visit to Barcelona every year is expected to foster the collaborative aspects of the project. The project involves psychophysics and large-scale electrophysiology in non-human primates, combined with computational approaches. The goal is to elucidate neural mechanisms for the visual-motor control of steering. Successful candidates will join a highly dynamic and collaborative group at the Center for Visual Science (https://www.cvs.rochester.edu) with strong theoretical/computational collaborations with the laboratories of Moreno-Bote and Drugowitsch, and expected extended visits to their labs. Previous work from our group has made fundamental contributions to our understanding of the neural basis of motion perception, depth perception, multisensory integration, self-motion perception, and perceptual decision-making ( https://pubmed.ncbi.nlm.nih.gov/?term=deangelis_gc&sort=date&size=100) Candidates are expected to have a background in neuroscience, experimental psychology, biomedical engineering, or a related field. Previous research experience in systems neuroscience is desirable, although it is not necessary. Candidates should submit their CV, a brief statement of research interests, and the names and contact information for three references to gdeangelis(a)ur.rochester.edu. -- Rubén Moreno Bote Serra Húnter Professor Director of the Theoretical and Cognitive Neuroscience Group 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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PhD modelling brain learning
by O'Donnell, Cian Dec. 2, 2022

Dec. 2, 2022

Our group at Ulster University are looking for a computational neuroscience PhD student for a project on “Discovering the rules of neural learning by computer simulations of brain biophysics and deep neural networks.” You will use multiscale computer simulations of electro-chemical signalling in neurons, synapses, and astrocytes to understand how the physical arrangement of different cell types affects brain learning. You can then use more abstract deep neural network models to study the circuit functions of these mechanisms for learning and memory. More details including reading material here: https://www.ulster.ac.uk/doctoralcollege/find-a-phd/1455716. The project will involve collaboration with Tom Bartol at the Salk Institute, La Jolla, California. You will join our research group which uses computational tools to do research on synaptic plasticity, learning and memory, autism, and neural data analysis methods: https://odonnellgroup.github.io. You will also be a member of the CNET team in the Intelligent Systems Research Centre (http://isrc.ulster.ac.uk) a community of researchers working across computational and cognitive neuroscience, neurotechnology, neuromorphic engineering, machine learning, robotics and related fields. We are based in the Derry campus of Ulster University. Derry a lively city of ~100K people on the River Foyle in Northern Ireland, UK. It has a highly affordable cost of living, thriving cultural scene, and access to spectacular coastal scenery and the great outdoors in Donegal and the north coast of Northern Ireland. To be eligible for funding, UK-based applicants should have or expect to obtain an upper second or first-class undergraduate or masters degree. International applicants should have a masters degree. Application deadline is 27th February 2023, for a Sept 2023 start. Application info here: https://www.ulster.ac.uk/doctoralcollege/find-a-phd/1455716. Please contact Cian (c.odonnell2(a)ulster.ac.uk<mailto:c.odonnell2@ulster.ac.uk>) if you are interested or have questions. -- Cian O’Donnell Lecturer in Data Analytics School of Computing, Engineering and Intelligent Systems Ulster University https://odonnellgroup.github.io This email and any attachments are confidential and intended solely for the use of the addressee and may contain information which is covered by legal, professional or other privilege. If you have received this email in error please notify the system manager at postmaster(a)ulster.ac.uk and delete this email immediately. Any views or opinions expressed are solely those of the author and do not necessarily represent those of Ulster University. The University's computer systems may be monitored and communications carried out on them may be recorded to secure the effective operation of the system and for other lawful purposes. Ulster University does not guarantee that this email or any attachments are free from viruses or 100% secure. Unless expressly stated in the body of a separate attachment, the text of email is not intended to form a binding contract. Correspondence to and from the University may be subject to requests for disclosure by 3rd parties under relevant legislation. The Ulster University was founded by Royal Charter in 1984 and is registered with company number RC000726 and VAT registered number GB672390524.The primary contact address for Ulster University in Northern Ireland is Cromore Road, Coleraine, Co. Londonderry BT52 1SA

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Kempner Institute Fellowships at Harvard University
by Cengiz Pehlevan Dec. 1, 2022

Dec. 1, 2022

The Kempner Institute at Harvard University is soliciting applications for the Kempner Institute Fellowships. We seek candidates with demonstrated ability and creativity who study one or more of the following areas: Foundations of intelligence, including mathematical and computational models of intelligence, cognitive theories of intelligence, computational neurobiology, and the neurobiological basis of intelligence. Applications of artificial intelligence, including natural language processing, visual scene processing and analysis, and to the mechanistic analysis of high dimensional neural and behavioral data. The study of these applications can either be from an engineering standpoint (e.g. development of new methodologies or advancing the state of the art) as well as from a scientific one (e.g. achieving a better understanding of deep learning). The Fellowship is intended for early stage scientists and will provide them with opportunities for intellectual growth in a highly interdisciplinary and collaborative environment. The fellows will independently set their research agenda but are strongly encouraged to work between fields and collaborate with preeminent experts at the Kempner Institute and at Harvard, more generally. Fellows will be appointed for a term of up to 3 years, with an annual salary of $100,000 and up to $10,000 per year of research support. Fellows will have access to shared office space, world-class computational resources and engineering support. They will benefit from a wide and deeply-engaged community of scientists, as well as access to the breadth of resources and facilities available to members of Harvard University. See https://academicpositions.harvard.edu/postings/11860 <https://academicpositions.harvard.edu/postings/11860> for more information. For other postdoctoral opportunities at Harvard for researchers in ML/AI, please see this webpage https://mlfoundations.org/#opportunities <https://urldefense.proofpoint.com/v2/url?u=https-3A__mlfoundations.org_-23o…>

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