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PhD student position in Machine Learning: Theoretically motivated deep learning
by Tony Lindeberg 09 Dec '22

09 Dec '22

PhD student position in Machine Learning: Theoretically motivated deep learning At the Division of Computational Science and Technology at KTH we are seeking a new PhD student in Machine Learning / Computer Vision to handle scale-dependent information in image data. In our research, we develop deep networks for processing image data that handle scaling transformations and other image transformations in a theoretically well-founded manner. Our research in this area comprises both theoretical modelling of the influence of image transformations on different architectures for deep networks as well as experimental evaluations of such networks on benchmark datasets to explore their properties. The work also comprises the creation of new benchmark datasets, to enable characterization of properties of deep networks that are not covered by existing datasets. For examples of our previous work in this area, see https://www.kth.se/profile/tony/page/deep-networks Within the scope of this PhD student position, you will work on and contribute to the research frontier regarding scale-covariant or scale-equivariant deep networks and/or deep networks parameterised in terms of Gaussian derivatives, on specific research topics that we choose together within the scope of the research project ”Covariant and invariant deep networks” that finances this position. The overall goal is to develop new architectures for deep networks that can generalise to scaling variations that are not spanned by the training data, and which can achieve higher robustness to variabilities in test data, as well as enable more efficient training with lower requirements concerning the amount of training data. The candidate should have very good knowledge in mathematics (analysis and linear systems, which we use for modelling convolution transformations and geometric image transformations) as well as in structured programming to write code that is easy to use for making experiments with, maintain and develop and share with colleagues. You must have very good knowledge about programming deep networks in Python, PyTorch is meritorious. Knowledge in computer vision and image analysis is strongly meritorious. For further information and information about how to apply, see https://www.kth.se/en/om/work-at-kth/lediga-jobb/what:job/jobID:567595/wher… [cid:FD2B374F-C472-4895-ADA7-B3CD5419FD22@csc.kth.se] Tony Lindeberg Professor of Computer Science — Computational Vision KTH Royal Institute of Technology Computational Brain Science Lab Division of Computational Science and Technology, CST SE-100 44 Stockholm, Sweden Phone: +46 8 790 6205 https://www.kth.se/profile/tony/

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December 15 Deadline; Wu Tsai Postdoctoral Fellowship
by giovanna.guerrero-medina＠yale.edu 09 Dec '22

09 Dec '22

The deadline to apply for a Wu Tsai Postdoctoral Fellowship is December 15, 2022. Please share the program details and the attached flyer with soon-to-be or recent PhDs outside of Yale who are enthusiastic about interdisciplinary research focused on cognition. The program provides a generous stipend for up to three years, funding for training and relocation, cohort-based professional development activities, and access to state-of-the-art facilities at Yale dedicated to integrative studies of the mind. International applicants are welcome. The Wu Tsai Postdoctoral Fellowship features opportunities for experimentalists and computationalists. The Computational Track is designed for scientists with expertise in computer science, data science, machine learning, artificial intelligence, applied math, or related fields who want to pursue independent research projects with Yale labs and use their skills to further our understanding of human cognition. The Experimental Track is for scientists wishing to work on co-mentored long-term projects in defined and compelling interdisciplinary neuroscience areas. Visit the Institute's website for a complete list of research projects. We encourage applications from scientists interested in contributing to diversity, equity, and inclusion in science. Find more information, past awardees, and application instructions here: https://wti.yale.edu/initiatives/postdoctoral. Best, Giovanna Guerrero-Medina, PhD She/Her/Ella Assistant Director for Diversity Equity & Inclusion, Wu Tsai Institute at Yale giovanna.guerrero-medina(a)yale.edu wti.yale.edu

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Announcing Okinawa/OIST Computational Neuroscience Course 2023
by Erik De Schutter 08 Dec '22

08 Dec '22

OKINAWA/OIST COMPUTATIONAL NEUROSCIENCE COURSE 2023 Methods, Neurons, Networks and Behaviors June 19 to July 6, 2023 Okinawa Institute of Science and Technology Graduate University, Japan https://groups.oist.jp/ocnc <https://groups.oist.jp/ocnc> The aim of the Okinawa/OIST Computational Neuroscience Course is to provide opportunities for young researchers with theoretical backgrounds to learn the latest advances in neuroscience, and for those with experimental backgrounds to have hands-on experience in computational modeling. We invite graduate students and postgraduate researchers to participate in the course, held from June 19th through July 6th, 2023 at an oceanfront seminar house of the Okinawa Institute of Science and Technology Graduate University. Applications are through the course web page (https://groups.oist.jp/ocnc <https://groups.oist.jp/ocnc>) only; January 1 - January 31, 2023. Applicants will receive confirmation of acceptance end of March. Like in preceding years, the 18th OCNC will be a comprehensive three-week course covering single neurons, networks, and behaviors with ample time for student projects. The first week will focus exclusively on methods with hands-on tutorials during the afternoons, while the second and third weeks will have lectures by international and local experts. The course has a strong hands-on component based on student proposed modeling or data analysis projects, which are further refined with the help of a dedicated tutor. Applicants are required to propose their project at the time of application. There is no tuition fee. The sponsor will provide lodging and meals during the course and may provide partial travel support. We hope that this course will be a good opportunity for theoretical and experimental neuroscientists to meet each other and to explore the attractive nature and culture of Okinawa, the southernmost island prefecture of Japan. Invited faculty: • Upinder Bhalla (NCBS, India) • Claudia Clopath (Imperial College London, UK) • Erik De Schutter (OIST) • Tomoki Fukai (OIST) • Yukiko Goda (OIST) • Mike Häusser (University College London, UK) • Bernd Kuhn (OIST) • Jinny Kim (KIST, South Korea) • Sam Reiter (OIST) • Greg Stephens (OIST) • Kazumasa Tanaka (OIST) • Marylka Yoe Uusisaari (OIST) • more to be announced

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6 PhD positions available in biomimetic embodied AI
by Thomas Nowotny 07 Dec '22

07 Dec '22

Dear Comp-Neuro community, We are offering 6 PhD studentships in our unique be.AI doctoral training centre in biomimetic embodied AI (http://www.sussex.ac.uk/ccnr/be_ai) at the University of Sussex in Brighton. Deadline: 23 February 2023 Apply online: https://www.sussex.ac.uk/study/phd/apply Full details at https://www.sussex.ac.uk/study/fees-funding/phd-funding/view/1403-Leverhulm…. Kind regards, Thomas -- Prof. Thomas Nowotny Head of AI Research Group CCNR, Sussex Neuroscience Phone: +44-1273-678593 Engineering and Informatics, Fax: +44-1273-877873 University of Sussex, Falmer, Brighton BN1 9QJ sussex.ac.uk/informatics/tnowotny<http://sussex.ac.uk/informatics/tnowotny> <../../owa/redir.aspx?C=9e11bb0e527242938402b42d9b5498ea&URL=http%3a%2f%2fsussex.ac.uk%2finformatics%2ftnowotny> I support the University of Sussex Community Pledge, as I continue to help those around me during the pandemic. Small acts of collaboration, kindness and integrity can make a big difference. www.sussex.ac.uk/community-pledge<http://www.sussex.ac.uk/community-pledge>

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PhD on neural modelling of conscious perception
by Howard Bowman 07 Dec '22

07 Dec '22

PhD position, University of Birmingham: Identifying the Role of Conscious Perception, a Neuroimaging and Computational Investigation Howard Bowman and Damian Cruse, School of Psychology, University of Birmingham are seeking applications for this PhD project, which is competition-funded under the Midlands Integrative Biosciences Training Partnership (supported by the UK Biotechnology and Biological Sciences Research Council). The deadline for applications is Friday, January 20, 2023; a percentage of the available scholarships can be allocated to non-UK students. Informal enquires can be made to H.Bowman(a)kent.ac.uk<mailto:H.Bowman@kent.ac.uk>. The question of what conscious perception is for remains a key issue for science. In fact, a substantial part of the scientific study of consciousness has focused on showing how sophisticated subconscious processing can be, seemingly leaving little room for a "special" purpose for conscious experience. We have recently presented evidence that the subconscious brain is limited in its capacity to represent episodic information (Avilés, Bowman & Wyble, 2020; Bowman & Avilés, In Press; Bowman et al, 2014). We now have extensive behavioural evidence for this hypothesis. We are thus at a perfect stage to 1) characterise the neural correlates (with fMRI, MEG or EEG) that support this formation of episodic memories, and 2) explain these findings with the Simultaneous Type/ Serial Token (STST) model (Bowman & Wyble, 2007), a neural network model of temporal attention. We are proposing a PhD to work on one or both of these topics. More details can be found at, https://warwick.ac.uk/fac/cross_fac/mibtp/pgstudy/phd_opportunities/neurosc… https://warwick.ac.uk/fac/cross_fac/mibtp/ -------------------------------------------- Professor Howard Bowman (PhD) Professor of Cognition & Logic in Computing at Uni Kent, and Professor of Cognitive Neuroscience in Psychology at Uni Birmingham (honorary at Wellcome Centre for Human Neuroimaging, University College London) Centre for Cognitive Neuroscience and Cognitive Systems and the School of Computing, University of Kent at Canterbury, Canterbury, Kent, CT2 7NF, UK email: H.Bowman(a)kent.ac.uk<mailto:H.Bowman@kent.ac.uk> WWW: http://www.cs.kent.ac.uk/people/staff/hb5/ School of Psychology, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK

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Call for community review: The Essential Metadata for 3D BRAIN Microscopy metadata standards (3D-MMS)
by INCF 07 Dec '22

07 Dec '22

*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 07 Dec '22

07 Dec '22

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 06 Dec '22

06 Dec '22

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 05 Dec '22

05 Dec '22

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 04 Dec '22

04 Dec '22

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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