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Two Data Scientist positions in Marburg, Germany
by Dominik Endres Nov. 5, 2021

Nov. 5, 2021

We are offering *two Data Scientist*(m/f/d) positions as a part of the cluster project *The Adaptive Mind*at the Philipps-Universität Marburg, Germany. The positions are associated with the Center of Mind, Brain and Behavior (CMBB) in Marburg. If you are interested in high-performance computing, machine learning and data management for large, interdisciplinary projects, then one of these jobs might be for you. Please contact Prof. Dominik Endres, dominik.endres(a)uni-marburg.de <mailto:dominik.endres@uni-marburg.de>, for more information. The full job adverts can be found here: https://www.uni-marburg.de/de/universitaet/administration/verwaltung/dezern… <https://www.uni-marburg.de/de/universitaet/administration/verwaltung/dezern…> https://www.uni-marburg.de/de/universitaet/administration/verwaltung/dezern… <https://www.uni-marburg.de/de/universitaet/administration/verwaltung/dezern…> Application deadline is Nov. 26^th , 2021 regards, Dominik Endres -- Prof. Dr. Dominik Endres Theoretische Kognitionswissenschaft - Theoretical Cognitive Science FB 04 Psychologie Tel: 06421-28 23818

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Flatiron Research Fellows (Post-Docs), Center for Computational Neuroscience, Flatiron Institute
by Matthew Turner Nov. 4, 2021

Nov. 4, 2021

Flatiron Research Fellows (Post-Docs), Center for Computational Neuroscience <https://www.simonsfoundation.org/flatiron/center-for-computational-neurosci…>, Flatiron Institute New York, New York ORGANIZATIONAL OVERVIEW The Simons Foundation is a private foundation established in 1994 in New York City. With assets of approximately $2 billion and an annual grants and programs budget of $230 million, the foundation is dedicated to advancing the frontiers of research in mathematics and the basic sciences. The Flatiron Institute is a major, new internal scientific unit of the Simons Foundation, focused on the computational aspects of a wide range of basic science. The mission of the Flatiron Institute is to advance scientific research through computational methods, including theory, modeling, simulation and data analysis. The Flatiron Institute currently consists of five centers: the Center for Computational Astrophysics (CCA); the Center for Computational Biology (CCB); the Center for Computational Quantum Physics (CCQ); the Center for Computational Mathematics (CCM); and the Center for Computational Neuroscience (CCN). The Institute staff is composed of research scientists at various stages of their careers from recent Ph.D.s through senior scientists, software engineers and support staff. We host a vigorous visitor program and interact regularly with scientists from neighboring institutions. POSITION SUMMARY Applications are invited for Flatiron Research Fellowships (FRF) at the Center for Computational Neuroscience. The CCN FRF program offers the opportunity for postdoctoral research in areas that have strong synergy with one or more of the existing research groups at CCN or other centers at the Flatiron Institute. CCN FRF’s will be assigned a primary mentor from a CCN research group or project, though affiliations and collaborations with other research groups within CCN and throughout the Flatiron Institute are encouraged. In addition to carrying out an independent research program, Flatiron Research Fellows are expected to: disseminate their results through scientific presentations, publications, and software release, collaborate with other members of the CCN or Flatiron Institute, and participate in the scientific life of the CCN and Flatiron Institute by attending seminars, colloquia, and group meetings. Flatiron Research Fellows may have the opportunity to organize workshops and to mentor graduate and undergraduate students. The mission of CCN is to develop theories, models, and computational methods that deepen our knowledge of brain function — both in health and in disease. CCN takes a “systems" neuroscience approach, building models that are motivated by fundamental principles, that are constrained by properties of neural circuits and responses, and that provide insights into perception, cognition and behavior. This cross-disciplinary approach not only leads to the design of new model-driven scientific experiments, but also encapsulates current functional descriptions of the brain that can spur the development of new engineered computational systems, especially in the realm of machine learning. CCN currently has research groups in computational vision, neural circuits and algorithms, neuroAI and geometry, and statistical analysis of neural data; interested candidates should review the CCN public website <https://www.simonsfoundation.org/flatiron/center-for-computational-neurosci…> for specific information on CCN’s research areas. Review of applications for positions starting between July and October 2022 will begin in mid-January 2022. Application Materials: - Cover letter (optional); - Curriculum Vitae with bibliography; - Research statement of no more than three pages describing past work and proposed research program. Applicants are encouraged to discuss the broad impact of the past and proposed research on computational neuroscience. Applicants should also indicate the primary CCN group(s) with which they’d seek to conduct research, and any desired affiliation with other Flatiron Centers. - Three (3) letters of recommendation submitted confidentially by direct email to ccnjobs(a)simonsfoundation.org Selection Criteria: Applicants must have a PhD in a related field or expect to receive their PhD before the start of the appointment. Applications will be evaluated based on 1) past research accomplishments 2) proposed research program 3) synergy of applicant’s expertise and research proposal topic with existing CCN staff and research programs. Education: - PhD in computational neuroscience or a relevant technical field such as electrical engineering, machine learning, statistics, physics, or applied math. Related Skills: - Flexible multi-disciplinary mindset; - Strong interest and experience in the scientific study of the brain; - Demonstrated abilities in analysis, software and algorithm development, modeling and/or scientific simulation; - Ability to do original and outstanding research in neuroscience; - Ability to work well independently as well as in a collaborative team environment. FRF positions are two-year appointments and are generally renewed for a third year, contingent on performance. FRF receive a research budget and have access to the Flatiron Institute’s powerful scientific computing resources. FRF may be eligible for subsidized housing within walking distance of the CCN. THE SIMONS FOUNDATION'S DIVERSITY COMMITMENT Many of the greatest ideas and discoveries come from a diverse mix of minds, backgrounds and experiences, and we are committed to cultivating an inclusive work environment. The Simons Foundation actively seeks a diverse applicant pool and encourages candidates of all backgrounds to apply. We provide equal opportunities to all employees and applicants for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, genetic disposition, neurodiversity, disability, veteran status or any other protected category under federal, state and local law. Application portal: https://simonsfoundation.wd1.myworkdayjobs.com/en-US/simonsfoundationcareer… Matthew B. Turner Manager for Center Administration | Center for Computational Neuroscience Pronouns: he/him/his *FLATIRON INSTITUTE* 162 Fifth Avenue Suite 308 New York, NY 10010 917.363.1095 *mobile* *simonsfoundation.org/flatiron/ <http://simonsfoundation.org/flatiron/>*

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Postdoc Fellowship in Data Science in Göttingen, Germany
by Ecker, Alexander Nov. 4, 2021

Nov. 4, 2021

The Campus Institute Data Science (CIDAS) at the University of Göttingen invites applications for two fellowships for outstanding young scientists to implement their own innovative research agenda in the field of Data Science and Artificial Intelligence. CIDAS promotes campus-wide interdisciplinary exchange and activities in the field of data science. The application deadline is Sunday, November 14th, 2021. In case of questions contact Alexander Ecker: ecker(a)cs.uni-goettingen.de *Funding Objectives:* CIDAS would like to support young scientists at an early stage of their career to develop independent projects and to create a perspective to work independently for several years at the Göttingen Campus in the field of Data Science. In particular, the collaboration between methodological, theoretical researchers and applied scientists at the Göttingen Campus and within CIDAS should be promoted. The applications should show a career perspective for the applicants and open a path to scientific independence and own third-party funding. *Who can apply:* Outstanding young scientists who are in the final phase of their PhD (last year) or early postdoc phase (maximum 2 years after the PhD) with an idea for their own research project in the field of Data Science. This can be in the fundamentals of Data Science, applied Data Science, or in the social science aspects of Data Science. This requires a planned collaboration with at least one member of CIDAS. Other collaborations with groups outside CIDAS are also possible and encouraged. If the applicant is not already a CIDAS member, he/she will be accepted into CIDAS upon approval of the application. The position can be used in particular for preparatory work for a subsequent application, e.g. for a junior research group. *Scope of funding:* Two fellowships will be awarded. The funding includes €75,000 each, which can be used, for example, to finance the applicant's own position. *Documents to be submitted:* 1. Description of the research idea (max. 5 pages), incl.: - Clearly defined content-related goals, comprehensible time schedule - Possible perspectives after the project, career perspectives, possibly plan for external funding - Planned collaboration with CIDAS members and other scientists - Innovation of the application 2. Curriculum vitae 3. Letter of recommendation from the supervisor or mentor, including a workplace (incl. infrastructure) commitment for the period to be funded Deadline: Sunday, November 14th, 2021 Application by email to: cidas(a)uni-goettingen.de -- Alexander Ecker Professor of Data Science Department of Computer Science • Campus Institute Data Science University of Göttingen • Max Planck Inst. for Dynamics and Self-Organization Goldschmidtstr. 1 • room 2.137 • 37077 Göttingen https://eckerlab.org • @alxecker • +49 551 39-21272

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PhD position at the Institute for Theoretical Physics, Goethe University Frankfurt
by Claudius Gros Nov. 4, 2021

Nov. 4, 2021

PhD position at the Institute for Theoretical Physics, Goethe University Frankfurt Applications are invited for a fully funded PhD position at the Institute for Theoretical Physics, Goethe University Frankfurt, Germany Fields: neurosciences, complex systems theory Application deadline: Dec 15, 2021 Supervisor: Prof. Dr. Claudius Gros We are developing new models and generative principles for complex systems, using a range of toolsets from dynamical systems theory, game theory, and the neurosciences. Examples are self-generated gaits for animals and robotic systems, criticality in autonomous networks, as well as Covid-19 modeling. Several subjects are available for the announced PhD thesis, depending on the background of the successful candidate. The work will include analytical investigations and numerical simulations. The candidates should have a Diploma/Master in physics with an excellent academic track record and good computational skills. Experience or strong interest in the fields of complex systems, dynamical systems theory, game theory and/or artificial or biological cognitive systems is expected. The degree of scientific research experience is expected to be on the level of a German Diploma/Master. The appointment will start in spring 2022, for three years. Interested applicants should submit a curriculum vitae and a list of publications to the address below. Prof. Claudius Gros Institute for Theoretical Physics Goethe University Frankfurt Max-von-Laue-Str. 1 60438 Frankfurt am Main, Germany cgr(a)itp.uni-frankfurt.de http://www.itp.uni-frankfurt.de/~gros General information on the University of Frankfurt and its employment policy: With its around 46,000 students and 4,600 employees, the Goethe University in Frankfurt is the largest university in the state of Hessen and an internationally renowned, important regional employer. Numerous quality and performance oriented internal reforms have been initiated in the recent years. The reorganized campuses for natural sciences and humanities offer an ideal environment for research and education. Since 2008, the Goethe University is a foundation under public law and enjoys full administrative autonomy.  The fixed-term employment of the academic staff is subject to the provisions of the Temporary Science Employment Law and the Hessian Higher Education Act. The University advocates gender equality and therefore strongly encourages women to apply. People with disabilities are given preference if equally qualified. -- ### ### Prof. Dr. Claudius Gros ### http://itp.uni-frankfurt.de/~gros ### ### Complex and Adaptive Dynamical Systems, A Primer ### A graduate-level textbook, Springer (2008/10/13/15) ### ### Life for barren exoplanets: The Genesis project ### https://link.springer.com/article/10.1007/s10509-016-2911-0 ###

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Faculty position in Data Science and Neuroengineering at Boston University
by Laura Lewis Nov. 3, 2021

Nov. 3, 2021

Dear colleagues, Forwarding the ad for our department's open position for an Assistant Professor: The College of Engineering at Boston University has embarked on a bold new strategic plan that will pursue excellence and impact along convergent and collaborative research themes while remaining committed to our institutional values regarding diversity, equity, and inclusion. The College anticipates two openings for tenure-track faculty positions at the level of Assistant Professor, one focusing on the convergent theme: Data Science in Neuroengineering. We are seeking a candidate whose research develops or uses methods from data science to advance knowledge of neuroscience in health and disease. Topics may include computational neuroscience, neurosignal processing, machine learning, image processing, artificial intelligence, or, more broadly, data science techniques in neuroscience. The ideal candidate will have a strong publication record in this convergent research theme and will be able to form links among the neuro- and systems-engineering strengths of the College’s Departments of Biomedical Engineering and Electrical and Computer Engineering, as well as the University’s strengths in the Data- and Neuro-Sciences. To apply: https://academicjobsonline.org/ajo/jobs/19046

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Postdoctoral position to study circuit mechanisms of adaptive learning at Dartmouth College
by Alireza Soltani Nov. 3, 2021

Nov. 3, 2021

The Computational and Cognitive Neuroscience Lab (CCNL) at Dartmouth College has an opening for an NIH-funded postdoctoral position to work on an exciting project on circuit mechanisms of reward-based learning under uncertainty. The project involves computational modeling and data analyses (behavioral and calcium imaging) in close collaboration with Alicia Izquierdo's lab at UCLA. Initial appointment is for one year with opportunity for renewal. The position is open to start immediately, but applications will be considered until the position is filled. A few recent relevant papers include: 1. Soltani A, Izquierdo A (2019). Adaptive Learning under Expected and Unexpected Uncertainty. Nature Reviews Neuroscience, 20(10): 635–644 2. Farashahi S, Donahue C, Hayden B, Lee D, Soltani A (2019). Flexible Combination of Reward Information across Primates. Nature Human Behaviour, 3: 1215–1224 3. Stolyarova A, Rakhshan M, Peters MA, Lau H, Soltani A, Izquierdo A (2019). Contributions of Anterior Cingulate Cortex and Basolateral Amygdala in Decision Confidence and Learning under Uncertainty. Nature Communications, 10:4704 4. Spitmaan MM, Seo H, Lee D, Soltani A (2020). Multiple Timescales of Neural Dynamics and Integration of Task-relevant Signals across Cortex. Proceedings of the National Academy of Sciences, 117 (36), 22522-22531 5. Trepka E, Spitmaan MM, Bari BA, Costa VD, Cohen JY, Soltani A (2021). Novel entropy-based metrics for predicting choice behavior based on local response to reward. Nature Communications (Accepted) [available on bioRxiv, 2021.05.20.445009v1] For more recent publications from the lab please visit http://ccnl.dartmouth.edu. Interested individuals should contact Alireza Soltani (soltani(a)dartmouth.edu) with their CV. Alireza Soltani, Ph.D. Associate Professor Department of Psychological and Brain Sciences Dartmouth College, NH Alireza.Soltani(a)Dartmouth.edu http://ccnl.dartmouth.edu Phone: 603-646-2998 Office: Moore 356

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BCI Un-Conference: Submission open
by Anja Meunier Nov. 2, 2021

Nov. 2, 2021

Dear colleagues, registration and abstract submission for the 3rd BCI Un-Conference is now open [1]. Abstract submissions are text-only. The length and format of the submissions are up to the authors - use whatever format you consider best for attracting up-votes! Important dates: - Submission deadline: December 3rd, 2021 at 11:59 pm (CET) - Voting period: December 6th, 2021 - December 12th, 2021 at 11:59 pm (CET) - BCI-UC event: January 27th, 2022, from 03:00 pm to 09:00 pm (CET) We will invite the authors of the top-voted abstracts to present at the un-conference. The 3rd BCI-UC will feature keynotes by Cynthia Chestek (University of Michigan) [2] and Thorsten Zander (TU Brandenburg) [3]. BCI-UC is an online un-conference that provides rapid dissemination of novel research results in the BCI community. Participants can submit abstracts to apply for 20 minutes presentation slots. Abstracts are not reviewed by a program committee. Rather, all registered participants can vote on which of the submitted abstracts they would like to see presented at the un-conference. Because the BCI-UC does not publish conference proceedings, submitted abstracts can report novel as well as already published work. Registration and attendance are free of charge. Presentations of the 1st and 2nd BCI-UC can be re-watched at [4] and [5]. All presentations will be streamed via Crowdcast [6] and can be accessed free of charge. Join us in supporting this novel community-driven dissemination of research results! The BCI-UC committee: Moritz Grosse-Wentrup Anja Meunier Philipp Raggam Jiachen Xu Links: [1] https://bciunconference.univie.ac.at/register-vote/ [2] https://scholar.google.com/citations?user=36sxAZEAAAAJ&hl=de [3] https://scholar.google.com/citations?hl=en&user=0E49HxYAAAAJ [4] https://bciunconference.univie.ac.at/past-events/1st-bci-uc/ [5] https://bciunconference.univie.ac.at/past-events/2nd-bci-uc/ [6] https://www.crowdcast.io/

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Postdoc position in Computational and Systems Neuroscience at Research Center Jülich, Germany
by Martina Reske Nov. 2, 2021

Nov. 2, 2021

The working group Statistical Neuroscience at INM-6 Computational and Systems Neuroscience<https://www.fz-juelich.de/inm/inm-6/EN/Home/home_node_INM6.html> at Research Center Juelich, Germany, led by Sonja Grün<https://www.fz-juelich.de/SharedDocs/Personen/INM/INM-6/EN/staff/Gruen_Sonj…> develops statistical methods for the analysis of experimental electrophysiological data from massively parallel electrophysiological recordings and leads the development of open source software tools for the analysis of activity data and validation of models on the population level. The department aims to fill a postdoctoral position that is responsible for the analysis of massively parallel spike and LFP data acquired in a collaborative project with CNRS-AMU, Marseille. Your Job: • Analysis of massively parallel spike and LFP data from the Vision for Action project (visuo-motor integration across areas) • Adaptation of machine learning algorithms and/or further development of methods for the analysis of these neuronal multichannel data • Development of methods for quantifying the relationship between spike patterns and LFP/ECoG data • Optimization and adaptation of neuronal network model in NEST for the comparison of experimental and simulated activity data • Implementation of data analysis tools in Python and integration of the codes into the shared analysis library Elephant • Contribution to the data analysis pipeline, under FAIR principles • Cooperation with experimental collaboration partners • Integration of the work into Ebrains / HBP • Presentation of project results at international conferences • Scientific and administrative project coordination • Support in the supervision of PhD students Your Profile: • MSc in physics, data science, mathematics or computer science; PhD in computational neuroscience, applied mathematics, physics or related • Detailed knowledge of neuroscientific concepts, especially in neuronal dynamics, statistical analysis of neuronal activity and dynamics • Expertise in network modelling at different spatial levels • Experience with large-scale data-science activities and scientific programming, especially Python • Fluent in spoken and written English • Experience in scientific publishing in a related field • Proactive working style, confident appearance and communication skills, high social competence and ability to work cooperatively in a team The position is initially for a fixed term of 2 Jahre years. Salary and benefits in conformity with the provisions of the Collective Agreement for the Civil Service (TVöD, salary grade 13-14). FZ Jülich promotes equal opportunities and diversity in its employment relations. We also welcome applications from disabled persons. Please apply via our recruitment system<https://www.fz-juelich.de/portal/EN/Careers/application/_node.html?cms_hre_…> under reference number: 2021-323. Martina Reske -- Dr. Martina Reske Scientific Coordinator Institute of Neuroscience and Medicine (INM-6) Computational and Systems Neuroscience & Institute for Advanced Simulation (IAS-6) Theoretical Neuroscience Jülich Research Centre and JARA Jülich, Germany Work +49.2461.611916 Work Cell +49.151.26156918 Fax +49.2461.619460 www.csn.fz-juelich.de<http://www.csn.fz-juelich.de> ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ Forschungszentrum Juelich GmbH 52425 Juelich Sitz der Gesellschaft: Juelich Eingetragen im Handelsregister des Amtsgerichts Dueren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Volker Rieke Geschaeftsfuehrung: Prof. Dr.-Ing. Wolfgang Marquardt (Vorsitzender), Karsten Beneke (stellv. Vorsitzender), Prof. Dr. Astrid Lambrecht, Prof. Dr. Frauke Melchior ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------

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The Gatsby Unit PhD programme
by Maneesh Sahani Nov. 2, 2021

Nov. 2, 2021

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

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Master in Brain and Cognition, Barcelona
by Ruben Moreno Bote Nov. 2, 2021

Nov. 2, 2021

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>

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job: machine learning research scientist at NIMH
by Francisco Pereira Nov. 2, 2021

Nov. 2, 2021

## 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!

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postdoc position on brain-machine interfaces at NYU & UO
by Luca Mazzucato Nov. 1, 2021

Nov. 1, 2021

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

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Modellers Workshop for the Brain Dynamics Toolbox
by Stewart Heitmann Oct. 31, 2021

Oct. 31, 2021

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.

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Postdoc in Brain Computer Interfaces, Melbourne, Australia
by David Grayden Oct. 28, 2021

Oct. 28, 2021

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.

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Job Posting: MindCORE Postdoctoral Research Fellowships at UPenn
by Calvert, Heather J Oct. 26, 2021

Oct. 26, 2021

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>

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Postdoc in computational cognitive neuroscience with human neurons in Utah
by ELLIOT H SMITH Oct. 26, 2021

Oct. 26, 2021

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

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NEXT WEEK: New Approaches to 3D Vision, 1st-4th Nov 2021, Royal Society online meeting
by Linton, Paul Oct. 26, 2021

Oct. 26, 2021

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)

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WWNeuRise series on the neuroscience of navigation
by William Podlaski Oct. 25, 2021

Oct. 25, 2021

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)

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Neuromatch Conference 4.0, Submission deadline Oct 25, conference Dec 1-2
by Rozell, Christopher J Oct. 22, 2021

Oct. 22, 2021

*****Deadline fast approaching for NMC 4!***** After three conferences in 2020, Neuromatch is pleased to be holding our fourth on December 1-2, 2021. Neuromatch 4.0 will be focused on Computational Neuroscience and will be similar to the scope of the first two NMC events in spring 2020. Agendas from previous NMC editions (1.0, 2.0 and 3.0) can be found on the Agenda from the conference website under the gear icon. The scope of NMC4 includes computational neuroscience and machine learning work that has a biological link. Registration costs are set at 15USD to cover technical costs, and if this is a difficulty, the fee can be waived without question. Each of our conferences has led the way in providing new innovations to the virtual conference space, and this year we are excited to offer you: * A combination of the virtual with the in-person conference experiences. You are encouraged to host or attend a local meetup, bringing people together to enjoy the conference, without the incredible economic and environmental costs of flying around the world. * The maintalks will be hosted on Crowdcast. Instead of posters, we offer flash talks (brief pre-recorded videos), and dedicated meet up times for discussion within Discord. * NMC for kids: a special session of talks for a younger audience and the young at heart interested in neuroscience. * We are developing new mechanisms to connect talks in the conference to corresponding preprints on bioRxiv, and we will provide links to preprints on other platforms as well. Read more at http://conference.neuromatch.io/ Important dates: * October 7, 2021: Registration and submission opens * October 25, 2021: Abstract submission deadline * Early November: local meetups portal opens * November 1 - 2, 2021: Abstract acceptance and live talk selection news * November 12, 2021: Video submission deadline for flashtalks * December 1 - 2, 2021: NMC 4.0 We look forward to seeing you at NMC 4.0! All the best, Neuromatch Conference Organizing Committee

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PhD Student Position for in-vivo Neurophysiology
by Alexander Maÿe Oct. 22, 2021

Oct. 22, 2021

PhD Student Position for in-vivo Neurophysiology The Department of Neurophysiology and Pathophysiology (head: Prof. Dr. Andreas K. Engel) at the University Medical Center Hamburg-Eppendorf (UKE) aims to fill a doctoral researcher (PhD student) position for in-vivo neurophysiology. The vacant position is part of the Marie-Curie training network “European School of Network Neuroscience (euSNN)” (http://www.eusnn.eu <http://www.eusnn.eu/>) and is for a project on modulation of cortical networks by optogenetic approaches. Contract duration will be 3 years, with a salary level according to the EU regulations for Marie-Curie Training Networks. The key research theme at the Department of Neurophysiology and Pathophysiology is the large-scale dynamics of cortical and subcortical networks which is addressed by combining electrophysiological and neuroimaging methods. The specific focus lies on the study of functional and effective connectivity in brain networks. Research at the Department aims to demonstrate and understand the functional role of dynamic large-scale coupling for perception, cognition and action. To this end, ongoing projects also test hypotheses on causal mechanisms by modulation of networks and connectivity. Furthermore, the Department has a strong interest in the pathophysiological relevance of neural synchrony and changes of large-scale coupling in brain disorders. Further information can be found at https://www.uke.de/neurophysiologie <https://www.uke.de/neurophysiologie> and http://www.40hz.net <http://www.40hz.net/>. At the UKE, the Department is embedded in an excellent environment for state-of-the-art network neuroscience, including multiple neuroimaging and animal research facilities, and excellent cooperation partners in all fields of clinical, theoretical and basic neuroscience. The new lab member will join a team with extensive expertise in in-vivo multisite recordings, connectivity analysis and network modulation using electrical and optogenetic stimulation approaches. The focus of the project will be on optogenetic modulation of oscillations and functional connectivity in cortical networks in anesthetized and behaving ferrets. The selected candidate will become a member of the euSNN network (http://www.eusnn.eu <http://www.eusnn.eu/>), which involves leading neuroscience labs as well as industrial partners from seven European countries and offers rich possibilities for interdisciplinary training and cooperation in network neuroscience. Candidates should have or expect a master in neuroscience, biology or related disciplines. Training in neurophysiology, optogenetics and/or data analysis methods is a plus. The Dept. of Neurophysiology and Pathophysiology is committed to diversity and seeks applications from qualified individuals regardless of their demographic status, gender, or cultural background. Applications from severely disabled persons with equivalent qualifications will be given preference. Applications should include a motivation letter, a CV, copies of university degrees and a transcript of course records. Please send your application materials as PDF (ideally in one file) to: ak.engel(a)uke.de <mailto:ak.engel@uke.de>. Prof. Dr. Andreas K. Engel Dept. of Neurophysiology and Pathophysiology University Medical Center Hamburg-Eppendorf -- _____________________________________________________________________ Universitätsklinikum Hamburg-Eppendorf; Körperschaft des öffentlichen Rechts; Gerichtsstand: Hamburg | www.uke.de Vorstandsmitglieder: Prof. Dr. Burkhard Göke (Vorsitzender), Joachim Prölß, Prof. Dr. Blanche Schwappach-Pignataro, Marya Verdel _____________________________________________________________________ SAVE PAPER - THINK BEFORE PRINTING

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Postdoc in comp. neuroscience - learning dynamics - Ruhr University Bochum, Germany
by Vinita Samarasinghe Oct. 22, 2021

Oct. 22, 2021

Prof. Sen Cheng, Institute for Neural Computation at the Ruhr University Bochum, invites applications for a full time *Postdoctoral position* (TV-L E13) in Computational Neuroscience. The position starts on July 1, 2022 and is funded for three years. The position is part of the Collaborative Research Center “Extinction Learning” (SFB 1280 <https://sfb1280.ruhr-uni-bochum.de/en/home/>) and entails the following duties: * analyze learning dynamics in behavioral, neural, and psychophysiological data, which will be collected by other projects within the SFB 1280, * compare the learning dynamics between individuals, species, learning phases and learning paradigms, * develop algorithms to analyze the learning dynamics, * develop and study computational models of learning dynamics, * coordinate research with other participating projects. Candidates must have: * a doctorate degree in neuroscience, physics, mathematics, electrical/biomedical engineering or a closely related field, * relevant experience in mathematical modeling, * excellent programming skills (e.g., Python, C/C++, Matlab), * excellent communication skills in English, * the ability to work well in a team. Research experience in neuroscience would be a further asset. The position is third party funded and does not have any formal teaching duties attached. The research group is highly dynamic and uses diverse computational modeling approaches including biological neural networks, cognitive modeling, and machine learning to investigate learning and memory in humans and animals. For further information see www.rub.de/cns. The Ruhr University Bochum is home to a vibrant research community in neuroscience and cognitive science. The Institute for Neural Computation is an independent research unit and combines different areas of expertise ranging from experimental and theoretical neuroscience to machine learning and robotics. The Institute for Neural Computation focuses on the dynamics and learning of perception and behavior on a functional level but is otherwise very diverse, ranging from neurophysiology and psychophysics over computational neuroscience to machine learning and technical applications. Please send your application, including CV, transcripts and research statement electronically, as a *single PDF file*, to *samarasinghe(a)ini.rub.de*. In addition, at least two academic references must be sent independently to the above email address. The deadline for applications is *January 2, 2022*. Travel costs for interviews will not be reimbursed. The Ruhr University Bochum is committed to equal opportunity. We strongly encourage applications from qualified women and persons with disabilities. We are committed to providing a supportive work environment for female researchers, in particular those with young children. Our university provides mentoring and coaching opportunities specifically aimed at women in research. We have a strong research network with female role models and will provide opportunities to network with them. Wherever possible, events will be scheduled during regular childcare hours. Special childcare will be arranged if events have to be scheduled outside of regular hours, in case of sickness and during school or daycare closures. Where childcare is not an option parents will be offered a home office solution. If you have any questions please feel free to get in touch with Vinita Samarasinghe (contact below) -- Vinita Samarasinghe M.Sc., M.A. Science Manager Arbeitsgruppe Computational Neuroscience Institut für Neuroinformatik Ruhr-Universität Bochum, NB 3/73 Postfachnummer 110 Universitätstr. 150 D-44801 Bochum Tel: +49 (0)234 32 27996 Email: samarasinghe(a)ini.rub.de

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Western-Fields Seminar Series | Frances Skinner
by Lyle Muller Oct. 21, 2021

Oct. 21, 2021

The eighth talk in the 2021 Western-Fields Seminar Series in Networks, Random Graphs, and Neuroscience<http://www.fields.utoronto.ca/activities/21-22/western-fields> is next Thursday (28 October) at noon ET. Frances Skinner<https://www.skinnerlab.org/> (Krembil Research Institute) will give a talk titled “Tackling the cellular diversity in our brains” (abstract below). Dr. Skinner is a leader in computational neuroscience and has made fundamental contributions to the understanding of neural dynamics from single cells to whole networks. This seminar series features monthly virtual talks from a diverse group of researchers across computational neuroscience, physics, and graph theory. We are looking forward to talks from Alexander Lubotzky (Hebrew University of Jerusalem) in November and Jeannette Janssen (Dalhousie University) in December. Registration link: https://zoom.us/meeting/register/tJYuf-GppzkjHt0W5HMDpME2UpUiE7ntO5JS — How do we address the challenge of bringing about a cellular-based understanding of our brain workings? From a neurological disease perspective, this needs to be addressed as pathologies involve cellular specifics. The ‘brain hub’ hippocampus, an essential brain structure for learning and memory, generates robust rhythmic activities. However, figuring out how the multitude of cell types in the hippocampus contribute to these states is an immense challenge. In this talk, I will describe the modeling approaches we are taking to obtain a cellular-based understanding of theta (3-12 Hz) rhythms in the hippocampus, an essential element of the ‘phase-coding functional unit’ in the hippocampus. -- Lyle Muller http://mullerlab.ca

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Post doc in Cognitive-Computational Neuroscience at University College London (discrete and continuous human action control under threat)
by Dominik R. Bach Oct. 21, 2021

Oct. 21, 2021

*Post doc in Cognitive-Computational Neuroscience at University College London: discrete and continuous human action control under threat* We are looking for a research fellow in an ERC-funded research project "Action selection under threat - the complex control of human defence" led by Dr Dominik Bach (http://bachlab.org <http://bachlab.org>) and based at University College London, Max-Planck UCL Centre for Computational Psychiatry (https://www.mps-ucl-centre.mpg.de/en <https://www.mps-ucl-centre.mpg.de/en>) and Wellcome Centre for Human Neuroimaging (http://www.fil.ion.ucl.ac.uk/ <http://www.fil.ion.ucl.ac.uk/>). The overarching goal of the project is to understand the cognitive-computational control of human motor behaviour under acute, immediate threat. We investigate this in an immersive virtual reality (VR) environment, in which people can move to avoid a large number of different threats. As part of this project, the candidate will build and test explicit computational models of discrete and continuous action control and action updating under constraints of time pressure and unaffordable costs. We seek applicants with established cognitive-computational modelling skills and a PhD in computational neuroscience, robotics with focus on action planning, computer science/mathematics/physics with a focus on decision science, or in a related area. We are looking for an individual who is strongly motivated to pursue an academic career and is excited by the opportunities for personal and career development this position can provide. The post is available from October 2021 and funded for up to 3 years with initial appointment for 1 year. Starting salary is on UCL grade 7, ranging from £36,028 to £43,533 per annum, inclusive of London Allowance, superannuable. More information and access to the UCL online application portal: https://is.gd/VwTJCA <https://is.gd/VwTJCA> Please contact d.bach(a)ucl.ac.uk <mailto:d.bach@ucl.ac.uk> for any queries about the project or role. *Closing date: 16 July 2021* Interviews will be held remotely in July. Apologies for cross-posting. -- ----------------------- Dominik R Bach MBBS PhD Principal Research Fellow Max Planck UCL Centre for Computational Psychiatry and Ageing Research Wellcome Centre for Human Neuroimaging, University College London http://bachlab.org | @bachlab_cog

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Two PostDoc positions, computational and experimental, on focused ultrasound neuromodulation
by Marcus Kaiser Oct. 20, 2021

Oct. 20, 2021

Dear all, Two PostDoc positions for the development and experimental validation of computational models of the effects of human focused ultrasound neuromodulation are available in my lab. *About the project* This programme of work, using the NeuroFUS PRO equipment for focused ultrasound neuromodulation, will focus on developing a software framework for modelling the effects of brain stimulation. Our objectives are to establish models of the biological effect of focused ultrasound and to predict effects of stimulation in humans, based on experiments performed as part of this study at Nottingham, and non-human primates, based on data from collaborators. Validated models of stimulation effects will then be a starting point for personalized stimulation approaches. *Available RA positions* As part of this project, the lab of Prof. Marcus Kaiser ( http://www.dynamic-connectome.org/ ) is seeking talented and enthusiastic research assistants with a PhD awarded, or a PhD thesis about to be submitted, in computational biology or related subjects; prior experience in the neurosciences is desirable. Computational RA position: The research fellow will implement simulations of biological effects on non-invasive interventions on targeted brain regions and on indirect effects in the rest of the brain network. In addition, tools for comparing effects of stimulations within a computer model and effects observed in experimental studies will be developed. Experimental RA position: The research fellow will work on focused ultrasound experiments, will run simulations of the physical effects (pressure and thermal changes) of stimulation, and will perform the processing of neuroimaging data. *Research Environment* Nottingham “the home of MRI” offers an excellent environment for imaging ( https://www.nottingham.ac.uk/research/beacons-of-excellence/precision-imagi… and https://www.nottingham.ac.uk/research/groups/spmic/index.aspx ), is pioneering the use of neurotechnology for brain disorders ( http://mindtech.org.uk/ ), hosts the Institute of Mental Health ( https://www.institutemh.org.uk ), and has a large group of faculty members including four full professors (Stephen Coombes, Mark van Rossum, Mark Humphries, Marcus Kaiser) in the area of computational/mathematical neuroscience. *How to Apply*Apply before 2 November 2021 at https://jobs.nottingham.ac.uk/Vacancy.aspx?id=35657&forced=2 (experimental RA) https://jobs.nottingham.ac.uk/Vacancy.aspx?id=35654&forced=2 (computational RA) For informal queries, please contact Dr Marcus Kaiser, marcus.kaiser(a)nottingham.ac.uk Best, Marcus -- *Marcus Kaiser, Ph.D. FRSB* @ConnectomeLab <https://twitter.com/ConnectomeLab> *Professor of Neuroinformatics* *Precision Imaging Beacon, School of Medicine, University of Nottingham* Guanci Visiting Professor Rui Jin Hospital, Shanghai Jiao Tong University, China Book: Changing Connectomes https://mitpress.mit.edu/books/changing-connectomes Lab website: http://www.dynamic-connectome.org/ Neuroinformatics UK: http://www.neuroinformatics.org.uk/

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FLAIRS-35 CFP, May 15-18, 2022, Jensen Beach, Florida
by David B Oct. 20, 2021

Oct. 20, 2021

FLAIRS-35 Special Track on Neural Networks and Data Mining The Florida Artificial Intelligence Research Symposium (FLAIRS) is an interdisciplinary conference which features double-blind reviewing, free tutorials, and a warm and sunny venue. Abstract Due Date: January 17, 2022 Submission Due Date: January 24, 2022 Conference: May 15-18, 2022 Jensen Beach, Florida Website: https://sites.google.com/view/flairs-35-nn-dm-track/home URL: https://www.flairs-35.info/call-for-papers Papers are being solicited for a special track on Neural Networks and Data Mining at the 35th International FLAIRS Conference (https://www.flairs-35.info/home) This special track will be devoted to neural networks and data mining with the aim of presenting new and important contributions in these areas. Papers and contributions are encouraged for any work related to neural networks, data mining, or the intersection thereof. Topics of interest may include (but are in no way limited to): applications such as Pattern Recognition, Control and Process Monitoring, Biomedical Applications, Robotics, Text Mining, Diagnostic Problems, Telecommunications, Power Systems, Signal Processing; Intelligence analysis, medical and health applications, text, video, and multi-media mining, E-commerce and web data, financial data analysis, cyber security, remote sensing, earth sciences, bioinformatics, and astronomy; algorithms such as new developments in Back Propagation, RBF, SVM, Deep Learning, Ensemble Methods, Kernel Approaches; hybrid approaches such as Neural Networks/Genetic Algorithms, Neural Network/Expert Systems, Causal Nets trained with Backpropagation, and Neural Network/Fuzzy Logic applications such as Intelligence analysis, medical and health applications, text, video, and multi-media mining, E-commerce and web data, financial data analysis, cyber security, remote sensing, earth sciences, bioinformatics, and astronomy; modeling algorithms such as hidden Markov models, decision trees, neural networks, statistical methods, or probabilistic methods; case studies in areas of application, or over different algorithms and approaches; graph modeling, pattern discovery, and anomaly detection; feature extraction and selection; post-processing techniques such as visualization, summarization, or trending; preprocessing and data reduction; and knowledge engineering or warehousing. Questions regarding the track should be addressed to: David Bisant at bisant(a)umbc.edu, Steven Gutstein at s.m.gutstein(a)gmail.com, or Bill Eberle at weberle(a)tntech.edu.

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