May 2021 - Comp-neuro - lists.cnsorg.org

Up to 6 PhD fellowships in Cognitive Neuroscience at SISSA, Trieste, Italy, to start Oct, 2020
by Alessandro Treves 12 Oct '22

12 Oct '22

SISSA is an elite postgraduate research institution located in Trieste, Italy, and focused on Maths, Physics and Neuroscience. It operates in English: many among its students and faculty are not Italian. The Cognitive Neuroscience Department hosts 6 research labs that study the neuronal bases of time and magnitude processing, visual perception, motivation and intelligence, language and reading, tactile perception and learning, and neural computation. The Department is very inter–disciplinary; our approaches include behavioural, psychophysics, and neurophysiological experiments with humans and animals, as well as computational and mathematical models. Students with diverse backgrounds (physics, math, medicine, psychology, biology) are most welcome to apply. The Department has an exceptional track record with highly competitive funds (recent funding includes 4 ERC and 3 Human Frontiers grants) and publication in top journals (Nature, Science, PNAS, Current Biology). Recent placements after PhD include Harvard, MIT, Columbia and Princeton in the US; the NTNU, Manchester and Radboud in Europe; and Sydney University, Australia. Our alumni have been awarded 4 ERC grants, the 2015 Kandel Young Neuroscientist Prize and the 2017 ICTP Prize. More information about the Department is available at our website https://phdcns.sissa.it. The selection procedure is now open; to learn how to apply, please visit https://phdcns.sissa.it/admission-procedure. Please contact the PhD Coordinator (davide.crepaldi(a)sissa.it) and/or your prospective supervisor for more information and informal enquiries. -- Alessandro Treves SISSA, Cognitive Neuroscience, http://people.sissa.it/~ale/limbo.html if in, rm 241, via Bonomea 265, 34136 Trieste, Italy: +39-040-3787623

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Postdoc in neural data analysis
by Mark Humphries 26 Jun '22

26 Jun '22

A 3 year postdoc post is available in the lab of Prof Mark Humphries, at the University of Nottingham (UK) In this project, our aim is to test the overarching hypothesis that movement transitions are encoded by the same neural population reconfiguring its joint activity, for both rhythmic and discrete movements. We will tackle this question using newly-available population recordings during rhythmic movement transitions in Aplysia and discrete arm movement transitions in monkeys, The Humphries’ group researches fundamental insights into how the joint activity of neurons encodes information about and actions in the world. For more see: https://www.humphries-lab.org Queries: mark.humphries(a)nottingham.ac.uk Deadline: 5th September Full details, and to apply: https://jobs.nottingham.ac.uk/Vacancy.aspx?id=27005&forced=2 [http://jobs.nottingham.ac.uk/org/images/socialmedia.png]<https://jobs.nottingham.ac.uk/Vacancy.aspx?id=27005&forced=2> Job Vacancy at the University of Nottingham: Research Associate/Fellow (Fixed term)<https://jobs.nottingham.ac.uk/Vacancy.aspx?id=27005&forced=2> Applications are invited for a postdoctoral research fellow to join the Humphries’ group on the MRC-funded project “Uncovering the neural basis of movement transitions”. The Humphries’ group researches fundamental... jobs.nottingham.ac.uk Professor Mark Humphries | MRC Senior non-Clinical Fellow | Chair in Computational Neuroscience Lab: humphries-lab.org<https://www.humphries-lab.org/> Twitter: @markdhumphries Public blog: https://medium.com/the-spike This message and any attachment are intended solely for the addressee and may contain confidential information. If you have received this message in error, please contact the sender and delete the email and attachment. Any views or opinions expressed by the author of this email do not necessarily reflect the views of the University of Nottingham. Email communications with the University of Nottingham may be monitored where permitted by law.

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Explainable AI: Overcoming problems of Deep Learning problems with Adaptive Resonance
by Grossberg, Stephen 09 Apr '22

09 Apr '22

Dear Colleagues, There's currently a lot of interest in AI, notably Deep Learning, and in achieving autonomous adaptive intelligence. The following new article summarizes foundational problems of reliability and trustworthiness of Deep Learning, explains how Adaptive Resonance overcomes them, and outlines a blueprint for achieving autonomous adaptive intelligence: Grossberg, S. (2020). A path towards Explainable AI and autonomous adaptive intelligence: Deep Learning, Adaptive Resonance, and models of perception, emotion, and action. Frontiers in Neurobotics, June 25, 2020. https://doi.org/10.3389/fnbot.2020.00036 Best, Steve Grossberg

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Postdoc at the University of Leicester to work on human single cell recordings
by Quian Quiroga, Rodrigo (Prof.) 23 Nov '21

23 Nov '21

The Centre for Systems Neuroscience at the University of Leicester, UK, offers a 3-years postdoc position to study single cell recordings in humans – performed in epileptic patients for curative surgery. 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 Nature Reviews Neuroscience 2012), which are involved in declarative memory functions. For more details see: www.le.ac.uk/csn The successful candidate will contribute to performing recordings with patients in collaborating hospitals and the analysis of the data to investigate the role of these neurons in memory. He/She should have very good quantitative skills (data processing, and programing e.g. in Matlab) and a strong background or interest in neuroscience. He/She should be able to work both independently and as part of a research team within the Centre for System Neuroscience at Leicester and with our external collaborators. Informal enquiries are welcome and should be made to Paula Warrington, Research Centre Manager, csn(a)le.ac.uk or 0116 252 3249. To apply, please use this link: https://jobs.le.ac.uk/vacancies/1393/research-associate.html The applications should include a curriculum vitae and a brief description of their scientific interests The closing date for the applications is 21st October 2019. Cheers, Rodrigo Rodrigo Quian Quiroga Centre for Systems Neuroscience University of Leicester www.le.ac.uk/csn

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Job: Engineer in MEG-EEG signal processing and open-source software development
by Franco Pestilli 31 May '21

31 May '21

The Paris Brain Institute is recruiting a motivated individual to join the *MEEGbrainlife* project, introducing MEG and EEG data processing pipelines on the open-access brainlife.io cloud computing platform. This is a 18-24 months contract funded jointly by the French ANR and the American NIH under the international program call « Collaborative Research in Computational Neuroscience » (CR‐CNS). The successful candidate will be responsible for planning, developing, and maintaining *MEG‐EEG data processing Apps into brainlife.io <http://brainlife.io/>* and *contribute to innovative research projects* on the platform. In close collaboration with the expert members of the MEEGbrainlife consortium, he/she will define data specifications, code architecture, data and code output quality check procedures to set the groundwork for the rapid development of a full data processing pipeline for MEG‐EEG data into brainlife.io. *More information and contact* for the application available here: https://owncloud.icm-institute.org/index.php/s/MBrIpIFcH3F9lV5 *FRANCO PESTILLI*, *Ph.D.* | *Associate Professor* Department of Psychology <https://liberalarts.utexas.edu/psychology/index.php> | College of Liberal Arts <https://liberalarts.utexas.edu/> | The University of Texas at Austin <https://www.utexas.edu/> he/him | pestilli(a)utexas.edu | web <https://liberalarts.utexas.edu/psychology/faculty/fp4834> | GitHub <https://github.com/francopestilli> | brainlife.io CONFIDENTIALITY NOTICE: This e-mail message, including any attachments, is for the sole use of the intended recipient(s) and may contain confidential and privileged information. Any unauthorized review, use, disclosure or distribution is prohibited. If you are not the intended recipient, please contact the sender by reply e-mail and destroy all copies of the original message.

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pre- and post-doc neuromorphic fellowships at the Sevilla Microelectronics Institute
by bernabe 31 May '21

31 May '21

Dear all, The Neuromorphic group at IMSE (Sevilla Microelectronics Institute, Spain) wellcomes candidates to apply for pre- and post-docs fellowships on neuromorphic engineering. Please visit our web-site at www.imse-cnm.csic.es/neuromorphs to find out about our running projects, activities, and publications. More details on the fellowships (duration/salary/contact) is given at: http://www2.imse-cnm.csic.es/neuromorphs/index.php/News-and-position-openin… cheers, -- Bernabe Linares-Barranco, Director Instituto de Microelectrónica de Sevilla (IMSE-CNM), CSIC, Sevilla, Spain

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Job opening: Research Scientist - Computational Neuroscience and Machine Learning/AI
by Michiel Remme 30 May '21

30 May '21

Dear Colleagues, Our startup INAIT, based in Lausanne, Switzerland, is seeking a permanent and full-time Research Scientist at the intersection of computational neuroscience and machine learning/AI. Are you interested in developing new machine learning/AI methods based on neuroscientific insights, and apply them to business problems? Then come join us! Major duties and responsibilities: * Contribute to the research and development of the next generation of neuroscience-inspired machine learning/AI methods * Contribute to the development of computational models of detailed and/or simplified neuronal networks * Work closely with a team of computational neuroscientists, machine learning engineers and software developers towards business solutions Essential skills and experience required: * PhD in computational neuroscience or related field (or equal experience: Masters and 4+ years of research experience) * Research involving learning and/or dynamics in rate-based and/or spiking neural networks * Experience in machine learning using frameworks such as scikit-learn, PyTorch or TensorFlow * Successful publication record * Experience in Python code development * Experience using UNIX/Linux operating systems * Excellent team player * Fluent spoken and written English Preferred: * Experience with a computational neuroscience simulation framework such as NEST, NEURON or Brian * Experience in scientific computing on shared and/or distributed parallel machines * Experience in the software development life-cycle including unit testing, continuous integration, version control, debugging and documentation * Successful track record in designing, developing and maintaining software projects Where: Lausanne, Switzerland Start date: As soon as possible Activity rate: 100% Duration of contract: CDI Competitive salary & benefits Cutting edge research, Positive work environment, Hybrid work model (combination of WFH and work from the office) For applications visit apply.workable.com/inait<http://apply.workable.com/inait/> INAIT SA https://www.inait.ai<https://www.inait.ai/> Avenue du Tribunal Fédéral 34 1005 Lausanne Switzerland

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Call for papers for MLCN2021 workshop at MICCAI 2021
by MLCN Workshop 30 May '21

30 May '21

*Please find below the call for papers for the International Workshop of Machine Learning in Clinical Neuroimaging (MLCN) which is held virtually on the 27th of September 2021 at MICCAI 2021 in Strasbourg, France. We welcome contributions to novel machine learning methods and their applications to clinical neuroimaging data.* The submission deadline is *25 June 2021*, and all MLCN accepted papers will be eligible for the best paper award of 500 USD. For more information, please visit https://mlcnws.com/call-for-papers/*.* Best wishes, The MLCN 2021 steering and organizing committees Christos Davatzikos, Andre Marquand, Jonas Richiardi, Emma Robinson Ahmed Abdulkadir, Mohamad Habes, Seyed Mostafa Kia, Vinod Kumar, Jane Maryam Rondina, Chantal Tax, Thomas Wolfers ================================================================================================ Call for Papers The International Workshop of Machine Learning in Clinical Neuroimaging ( https://mlcnws.com/) a satellite event of MICCAI (https://miccai202 <https://miccai2021.org/>1 <https://miccai2020.org/>.org <https://miccai2021.org/>), calls for original papers in the field of clinical neuroimaging data analysis with machine learning. The two tracks of the workshop include methodological innovations as well as clinical applications. This highly interdisciplinary topic provides an excellent platform to connect researchers of varying disciplines and to collectively advance the field in multiple directions. In the machine learning track, we seek novel contributions that address current methodological gaps in analyzing high-dimensional, longitudinal, and heterogeneous clinical neuroscientific data using stable, scalable, and interpretable machine learning models. Topics of interest include but are not limited to: - Big data - Spatio-temporal brain data analysis - Structural data analysis - Graph theory and complex network analysis - Longitudinal data analysis - Model stability and interpretability - Model scalability in large neuroimaging datasets - Multi-source data integration and multi-view learning - Multi-site data analysis, from preprocessing to modeling - Domain adaptation, data harmonization, and transfer learning in neuroimaging - Unsupervised methods for stratifying brain disorders - Deep learning in clinical neuroimaging - Model uncertainty in clinical predictions - … In the *clinical neuroimaging *track*,* the applications of existing machine learning algorithms are evaluated to move towards precision medicine for complex brain disorders. The discovery of biological markers in medicine is an important challenge across different fields and various experimental procedures and designs are used to detect biological signatures that can be utilized for improvement in diagnostic, treatment, or for other beneficial ends. However, for most complex brain disorders, we do not have reliable biomarkers today. The application of advanced machine learning methods may help to reach this goal. Therefore, we invite the community to submit conference contributions on machine learning approaches with the goal to improve our understanding of complex brain disorders, moving the field closer towards precision medicine. Topics of interest include but are not limited to: - Biomarker discovery - Refinement of nosology and diagnostics - Biological validation of clinical syndromes - Treatment outcome prediction - Course prediction - Analysis of wearable sensors - Neurogenetics and brain imaging genetics - Mechanistic modeling - Brain aging - The presentation of clinical neuroimaging databases to stimulate developments in machine learning - … ------------------------------ Submission Process: The workshop seeks high-quality, original, and unpublished work that addresses one or more challenges described above. Papers should be submitted electronically in Springer Lecture Notes in Computer Science (LCNS) style (see https://miccai2021.org/en/PAPER-SUBMISSION-GUIDELINES.html for detailed author guidelines) using the CMT system at https://cmt3.research.microsoft.com/MLCN2021. The page limit is 8-pages (text, figures, and tables) plus up to 2-pages of references. We review the submissions in a double-blind process. Please make sure that your submission is anonymous. Accepted papers will be published in a joint proceeding with the MICCAI 2021 conference. ------------------------------ MLCN Special Issue at the MELBA journal: This year, we will invite the top accepted papers to submit an extended version of their contribution to the MLCN special issue at the Journal of Machine Learning for Biomedical Imaging (MELBA) <https://www.melba-journal.org/about>. The invited papers will go through an independent review process by the journal. ------------------------------ Best Paper Award: All MLCN accepted papers will be eligible for the best paper award. The recipient of the award will be chosen by the MLCN scientific committee based on the scientific quality, novelty, and clarity of contributions. The winner will be announced at the end of the workshop and will receive a 500 USD honorarium. ------------------------------ Important Dates: - Paper submission deadline: June 25, 2021, 11:59 PM Pacific Time - Notification of Acceptance: July 16, 2021 - Camera-ready Submission: July 30, 2021 - Workshop Date: September 27, 2021

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Postdoc in Cognitive and Systems Neuroscience
by Theresa Desrochers 28 May '21

28 May '21

Applications for Postdoctoral Research Associate are being sought for a unique opportunity to study sequential control in the laboratory of Dr. Theresa Desrochers in the Department of Neuroscience at Brown University. Successful candidates will have interest in human behavior, fMRI, TMS, computational psychiatry, and OCD. The Desrochers Lab provides a unique cross-level and cross-species training environment situated within a highly collaborative research environment fostered by Brown University and the Carney Institute for Brain Science. Prior experience in human neuroimaging and strong quantitative skills are preferred. All interested candidates regardless of level of experience with these methods are encouraged to apply. Applicants must hold a Ph.D. in Neuroscience, Cognitive Science, Psychology, or a related discipline or must show evidence that the Ph.D. will be completed before the start of the position. Brown University is an EEO/AA employer and encourages applications from minorities and women. Review of applications will begin immediately and will continue until the position is filled or the search is closed. For more information, please contact theresa_desrochers(a)brown.edu. Please apply via Interfolio at https://apply.interfolio.com/87606 <https://apply.interfolio.com/87606>. ~Theresa — Theresa M. Desrochers, Ph.D. Rosenberg Assistant Professor of Brain Science Departments of Neuroscience; Psychiatry and Human Behavior (courtesy) Carney Institute for Brain Science, Brown University http://neuroscience.brown.edu/desrochers

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PhD positions at Vrije Universiteit Amsterdam
by Avitabile, D. 28 May '21

28 May '21

Dear colleagues, The Department of Mathematics at the Vrije Universiteit Amsterdam invites applications for 2 PhD positions, in computational and analytical methods form neuroscience applications. One project concerns uncertainty quantification methods for spatially-extended models in neuroscience. The ideal candidate for this project has a passion for numerical methods (numerical analysis, scientific computing) and is keen to make an impact in a novel application for the neurosciences. Previous knowledge of neuroscience concepts is not a prerequisite, but a firm interest in learning about neuroscience models and applications is essential. The project will be co-supervised by Svetlana Dubinkina (VU), Gabriel Lord (Radboud University), and myself. The second PhD project is about multiple timescale analysis for neural fields, and it aims to develop slow-fast dynamical system methods for spatially-extended systems. The ideal candidate has a passion for dynamical system theory and is interested in applying bifurcation analysis to PDEs and integral equations. Previous knowledge of neuroscience concepts is not a prerequisite. The project will be cosujervised by Jan Bouwe van den Berg (VU) and myself. It will also involve a network of scientific collaborators: Mathieu Desroches (INRIA, Sophia Antipolis, France), Grégory Faye (University Paul Sabatier, Toulouse, France) and Martin Wechselberger (University of Sydney, Australia). More information can be found at the link below https://werkenbij.vu.nl/ad/phd-positions-in-mathematical-neuroscience/ngla4… The deadline for applications is the 13th of June 2021. Informal enquiries can be sent to d.avitabile(a)vu.nl Daniele Avitabile Associate Professor in Applied Mathematics Vrije Universiteit Amsterdam www.danieleavitabile.com

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