- Comp-neuro - lists.cnsorg.org

workshop organized by the Neuroscience Gateway project on October 5th starting at 8:30am at the campus of University of Chicago

by Majumdar, Amitava

We are organizing a workshop in Chicago on October 5th , 2024 starting at 8:30 am (Central time) and till 11:30am (Central time) at the campus of University of Chicago. The agenda is provided below. If you are interested in attending, please email Amit Majumdar (amajumdar(a)ucsd.edu) to receive the link to register. Registration is free but due to limited seatings, we are requesting registration and it will also provide the address of the location of the workshop. AGENDA (October 5th, 2024, University of Chicago) 8:30 AM - 8:45 AM Welcome 8:45 AM - 9:15 AM Title: Human Neocortical Neurosolver: A Software Tool for Cell and Circuit Level Interpretation of MEG/EEG signals Authors: Nicholas Tolley, Stephanie Jones Affiliation: Brown University Abstract: MEG/EEG signals are correlated with nearly all healthy and pathological brain functions. However, it is still extremely difficult to infer the underlying cellular and circuit level origins. This limits the translation of MEG/EEG signals into novel principles of information processing, or into new treatment modalities for pathologies. To address this limitation, we built the Human Neocortical Neurosolver (HNN): an open-source software tool to help researchers and clinicians without formal computational modeling or coding experience interpret the neural origin of their human MEG/EEG data. The foundation of HNN is a biophysically-detailed neocortical model, representing a patch of neocortex receiving thalamic and corticocortical drive. The HNN model can be accessed through a user-friendly interactive graphical user interface (GUI) or through a Python scripting interface. Tutorials are provided to teach users how to begin to study the cell and circuit level origin of sensory event related potentials (ERPs) and low frequency rhythms. The package is available to install with a single command on PyPI (pip install hnn_core), is unit tested and extensively documented. HNN is additionally accessible through computing resources offered by the Neuroscience Gateway (NSG) enabling large simulation workloads. We will give an overview of the background of HNN, describe the newest features added to the software, and highlight recent research projects using HNN. 9:15 AM - 9:45 AM Title: The NEMAR Neuromagnetic Data, Tools, and Compute Resource Authors: Scott Makeig1, Kenneth Yoshimoto2, Choonhan Youn2, Dung Troung1, Subhashini Sivagnanam2, Amitava Majumdar2, Arnaud Delorme1 Affiliation: 1Swartz Center for Computational Neuroscience, 2San Diego Supercomputer Center, University of California San Diego Abstract: The recent BRAIN Initiative, funded by the Obama administration, propelled the creation of archives of publicly and other funded scientific data of all types. For human functional neuroimaging, the OpenNeuro.org archive was funded to collect and publicly share data of all types. Its creator, Russ Poldrack, is an fMRI expert. For other imaging modalities, NIMH funded projects to curate data contributed to OpenNeuro. Our NEMAR.org serves that purpose for 'neuroelectromagnetic' data (EEG, MEG, iEEG). Beyond simple data curation, publication of data quality measures and data visualization, NEMAR exemplifies what I believe should become the basic unit of open science, what I call the 'integrated data, tools, and compute resource' (datcor). By teaming with the Neuroscience Gateway team, NEMAR now supports users worldwide in identifying and performing sophisticated computations on increasing amounts of publicly available data - without need for at-best balky data downloads. 9:45 AM - 10:15AM Title: DANDI: Building a collaborative ecosystem for neuroscientific data Authors: Satrajit Ghosh Affiliation: McGovern Institute, MIT Abstract: The DANDI Archive is a community-oriented platform designed to support the sharing, analysis, and re-use of neurophysiology and microscopy data, using the BRAIN Initiative supported standards for data sharing. By providing an open, FAIR-compliant (Findable, Accessible, Interoperable, Reusable) ecosystem, DANDI facilitates collaborative research in neuroscience. It integrates diverse data types, from electrophysiology to imaging, ensuring that researchers can contribute, discover, access, visualize, and compute on standardized datasets seamlessly. This presentation will highlight the key features of DANDI, including its data management infrastructure, open-source tools, and how it promotes transparency, reproducibility, and interdisciplinary collaboration in neuroscience research. 10:15 AM - 10:30 AM BREAK 10:30 AM - 11:00 AM Title: Enhancing Perspectives in Neuroscience Research through Diverse Institutional Partnerships. Author: Elba Serrano Affiliation: New Mexico State University Abstract: Diversity in collaboration is expected to yield more inclusive and representative research outcomes and potentially address more varied needs within a field. By pooling knowledge and resources from different disciplines, institutions, and investigators, researchers can approach problems in neuroscience from multiple angles, leading to more comprehensive and innovative solutions. The nation's 700+ federally designated minority serving institutions (MSIs) comprise about 15% of all degree-granting institutions and educate over 5 million students. This presentation will introduce attendees to the rich constellation of MSIs with a spotlight on Hispanic serving institutions (HSIs), where 65% of the nation's Latino students seek degrees. Drawing on experiences as lead for the NSF HSI National STEM Resource Hub, the speaker will provide an overview of the benefits and challenges in developing collaborations with colleagues at MSIs, as well as strategies for identifying partners and developing authentic relationships that further neuroscience research. 11:00 AM - 11:30 AM Title: Bio-realistic modeling of the mouse primary visual cortex using large-scale datasets Authors: Shinya Ito1, Darrell Haufler1, Kael Dai1, Joe Aman1, Javier Galván Frail2, Guozhang Chen3, Claudio Mirasso2, Wolfgang Maass4, Anton Arkhipov1 Affiliation: 1. Allen Institute, Seattle, Washington, USA 2. IFISC, University deles Illes Balears, Palma de Mallorca, Spain 3. Peking University, Beijing, China 4. Graz University of Technology, Graz, Austria Abstract: Accurate models of cortical circuits facilitate a deeper understanding of how neural dynamics are shaped and maintained within the brain. We have developed an enhanced, biologically realistic model of the mouse primary visual cortex (V1), building on the framework established by Billeh et al. (Neuron, 2020). This updated model integrates new synaptic physiology data from Campagnola, Seeman et al. (Science, 2022; portal.brain-map.org/connectivity/synaptic-physiology) and detailed connectomics from the IARPA MICrONS dataset (www.microns-explorer.org) refining its connectivity and synaptic dynamics. The resulting model exhibits stable activity patterns before optimization. Moreover, we utilized TensorFlow-based optimization techniques to align model parameters with physiological data, including Neuropixels recordings, achieving key empirical targets such as firing rates and orientation selectivity. This improved model not only enhances our understanding of cortical processing but will also be made publicly available to support further research. ---------------------------------------------------------------------------------------------------- Organizers: Amit Majumdar, Subhashini Sivagnanam, Kenneth Yoshimoto San Diego Supercomputer Center, University of California San Diego Ted Carnevale, Neuroscience Department, Yale School of Medicine, Yale University Co-organizers: Kimberly Grasch and H. Birali Runesha, University of Chicago -----------------------------------------------------------------------------------------------------

Sept. 17, 2024

Workshop "Data-Driven Discovery: AI and Modeling in Biology" at the Allen Institute

by Anton Arkhipov

Dear Colleagues, We will be livestreaming the upcoming workshop "Data-Driven Discovery: AI and Modeling in Biology" organized by Anton Arkhipov (Allen Institute), Tatiana Engel (Princeton), Michael Brenner (Harvard/Google), and Stephen Saalfeld (Janelia). Hosted by the Allen Institute on September 23-25, 2024, the meeting brings together experts who will discuss how problems in biology are being solved using recent developments in both AI and modeling. Please see the streaming link at the meeting website: https://alleninstitute.org/events/data-driven-discovery-ai-and-modeling-in-… The goal of this meeting is to explore how problems in biology are being solved using cutting-edge computational approaches, with the focus on recent developments in both AI and modeling, including merging the two. Biology is a broad field. We aim to connect researchers across a wide range of computational biology to learn from each others’ approaches. Agenda is below (all times listed as Pacific Standard Time). ================================================== Monday, September 23, 2024 2:00–2:15pm Welcome and opening remarks 2:15–3:15pm KEYNOTE- David Baker, University of Washington Protein design for molecular recognition 3:15–3:45pm Bing Brunton, University of Washington Embodied intelligence through integrated neuromechanical models of natural behavior 3:45–4:15pm Andreas Tolias, Stanford University NeuroAI: Building Digital Twins of the Brain Tuesday, September 24, 2024 9:00–9:30am Matheus Viana, Allen Institute for Cell Science Towards a holistic and quantitative stem cell state landscape 9:30–10:00am Kim Stachenfeld, Columbia University/Google DeepMind Learning to Simulate and Control Fluid Dynamics with Graph Neural Networks 10:00–10:30am Armita Nourmohammad, University of Washington Learning the shape of the protein and immune universe 10:30-11:00am Break 11:00–11:30am Mariano Gabitto, Allen Institute for Brain Science Deep generative models for the multimodal analysis of single-cell datasets 11:30–12:00pm Roy Kishony, Technion-Israel Institute of Technology AI driven science 12:00–12:30pm Stefan Mihalas, Allen Institute Why is the activity in the brain so variable? 12:30-2:00pm Break 2:00–2:30pm Michael Elowitz, California Institute of Technology Many-to-many protein networks as flexible computational modules Wednesday, September 25, 2024 9:00–10:00am KEYNOTE- Emily Fox, Stanford University, insitro Machine Learning for Better Medicines 10:00–10:30am Xiaojun Li, Allen Institute for Immunology Application of AI in Immunology Research 10:30-11:00am Break 11:00–11:30am Gokul Upadhyayula, University of California Berkeley Navigating challenges and opportunities with high-resolution in vivo imaging 11:30–12:00pm Laura Driscoll, Allen Institute for Neural Dynamics Fast and slow learning in artificial and biological networks 12:00–12:30pm Eric Shea-Brown, University of Washington Assigning credit through the "other” connectome 12:30-2:00pm Break 2:00–2:30pm Viren Jain, Google Simulating a zebrafish brain with functional connectomics and AI 2:30–3:00pm Kristin Branson - Janelia Research Campus, Howard Hughes Medical Institute What can we learn from deep-learning-based forecasting models of biological time series? 3:00–3:30pm Ben Cowley, Cold Spring Harbor Laboratory Mapping model units to visual neurons reveals population code for social behavior ================================================== Best regards, Anton Arkhipov Investigator, Allen Institute

Sept. 17, 2024

Free hybrid workshop: Linking brain structure & function at the nanoscale

by Audrey Denizot

Dear all, The [ https://team.inria.fr/aistrosight/ | AIstroSight team ] from Inria Lyon, France, is organizing a hybrid workshop on September 26th-27th 2024 entitled "Linking brain structure & function at the nanoscale: an interdisciplinary workshop". This interdisciplinary workshop aims to bring together experts from diverse fields who contribute to improving our understanding of the nanoscale landscape of the nervous system and its impact on brain function, from volume electron microscopy to image analysis, machine learning, deep learning, and computational modeling. Registration is open until September 24th, free but mandatory following [ https://club-de-cellules-gliales.assoconnect.com/collect/description/450527… | this link ] . More information can be found on the workshop website: [ https://adenizot.github.io/workshops/ | https://adenizot.github.io/workshops/ ] Invited speakers: - Carles Bosch, The Francis Crick Institute, England - Corrado Cali, Neuroscience Institute Cavalieri Ottolenghi, Italy - Michael Chirillo, University of Texas, USA - Audrey Denizot, Inria, France - Erik De Schutter, Okinawa Institute of Science and Technology, Japan - Christel Genoud, Université de Lausanne, Switzerland - Daniel Keller, Ecole Polytechnique Fédérale de Lausanne, Switzerland - Constantin Pape, University of Göttingen, Germany - Karin Pernet-Gallay, Université Grenoble Alpes, France - Padmini Rangamani, University of California San Diego, USA - Chris Salmon, McGill University, Canada Best wishes, Audrey Denizot -- Audrey Denizot ------------------------------ PhD, Inria research scientist — — Project-Team AIstroSight — — [ https://team.inria.fr/aistrosight | https://team.inria.fr/aistrosight ] — — — Centre INRIA de Lyon — — — Campus La Doua Bâtiment CEI-2 56, Boulevard Niels Bohr - CS 52132 69603 Villeurbanne - France [ mailto:audrey.denizot@inria.fr | audrey.denizot(a)inria.fr ] | [ https://adenizot.github.io/ | Website ] | [ https://www.linkedin.com/in/audrey-denizot-180684201/ | LinkedIn ] | [ https://twitter.com/ADenizot | Twitter ]

Sept. 16, 2024

PhD and postdoc positions in the Zenke Lab at the FMI, Basel, Switzerland.

by Friedemann Zenke

We are looking for new team members! Please consider applying if you want to build models of how the brain learns and simulates a world model. We have several openings at PhD and postdoc levels, including a collaboration with the Keller Lab at the FMI on designing regulatory elements to target distinct neuronal cell types. For more information and example projects, see http://zenkelab.org/jobs Kind regards, Friedemann

Sept. 16, 2024

Faculty positions in Theory, Computation, Data Science at WashU

by Tavoni, Gaia

Cluster hire in Theory, Computation, and Data Science for Understanding Living Systems, Departments of Biology, Chemistry, and Physics, Washington University in St. Louis Washington University in St. Louis invites applications for tenure-track faculty positions at the rank of assistant or associate professor for a cluster hire in the area of theory, computation, and data science in the departments of Biology, Chemistry, and Physics. Life operates across a diversity of scales, from molecular-scale processes shaping cellular function to the delicate dynamic balance of our biosphere as a whole. System-level properties and processes are affected by interactions operating at all scales and between scales. Understanding these interconnected systems requires an interconnected and multidisciplinary research community. From AI-driven advances in protein structure and dynamics, to advanced imaging methods enabled by quantum sensing, to developing entirely new mathematical and computational frameworks to achieve insight from complex data, transformative advances in life sciences will require the synergistic work of scientists working across disciplinary boundaries. This cluster aims to create a hub of researchers using theoretical, computational, artificial intelligence, statistics, and data-science methods to advance life sciences from molecular to ecological scales. Applicants whose research synergizes with current areas of strength at Washington University will be favorably considered. Applicants whose research includes an experimental component but is primarily focused on developing theoretical, computational, and data-science methods will also be favorably considered. Candidates should have a Ph.D. in Biology, Chemistry, Physics, or a closely related field. Candidates for the rank of Associate Professor should have an outstanding academic record of research, publication, teaching, and service commensurate with tenure at this rank. Joint applications exhibiting a high degree of research synergy will be considered. Duties will include conducting research, teaching, advising students, and participating in departmental governance and university service. Diversity, equity, and inclusion are core values at Washington University, and we seek to create inclusive classrooms and environments in which a diverse array of students can learn and thrive. Applications should consist of a cover letter describing how the candidate’s research fits within the theme of the cluster; a detailed curriculum vitae; statements of research directions (3-5 pages), teaching interests (1 page), and contributions towards promoting an inclusive research culture or community at large (1 page); and contact information for at least three references. Applications should be submitted to https://apply.interfolio.com/152466 by Oct. 18, 2024 to receive full consideration. Washington University in St. Louis has a policy to recruit, hire, train, and promote persons in all job titles without regard to race, color, age, religion, sex, sexual orientation, gender identity or expression, national origin, protected veteran status, disability, or genetic information. *************************************************** Gaia Tavoni, PhD Assistant Professor of Neuroscience Washington University in St Louis ________________________________ The materials in this message are private and may contain Protected Healthcare Information or other information of a sensitive nature. If you are not the intended recipient, be advised that any unauthorized use, disclosure, copying or the taking of any action in reliance on the contents of this information is strictly prohibited. If you have received this email in error, please immediately notify the sender via telephone or return mail.

Sept. 14, 2024

Human Neocortical Neurosolver (HNN) Workshop at SFN

by Gao, Joyce

Dear all, We invite you to join us at SFN 2024 for a hands-on Human Neocortical Neurosolver (HNN) Workshop! HNN is a user-friendly software tool for interpreting the cell and circuit level origin of human MEG and EEG signals (Neymotin et al 2020, https://hnn.brown.edu) You can find out more about HNN and register here: https://hnn.brown.edu/workshop-registration/. Seats are limited, so if you are interested, we recommend signing up today! Our best, Jones Computational Neuroscience Lab Brown University, Carney Institute for Brain Science

Sept. 13, 2024

Research Assistant Position in Developmental Cognitive Neuroscience at American University, Washington DC

by Laurie Bayet

*Research Assistant Position in Developmental Cognitive Neuroscience at American University, Washington DC* The Developmental Cognitive Neuroscience Laboratory at American University, located in Washington DC and directed by Dr. Laurie Bayet ( https://www.bayetlab.com/) is currently accepting applications for a full-time, benefits-eligible Research Assistant position to assist on NSF and foundation-funded funded projects investigating infant visual cognition and social communication (e.g., NSF award # 2122961 <https://www.nsf.gov/awardsearch/showAward?AWD_ID=2122961>). The lab uses electro-encephalography (EEG), functional near-infrared spectroscopy (fNIRS), behavioral measures, and machine learning. The position is ideal for an individual seeking to deepen their research experience in preparation for graduate study. *Applicants should apply electronically at https://american.wd1.myworkdayjobs.com/AU/job/Main-Campus-Washington-DC/Res… <https://american.wd1.myworkdayjobs.com/AU/job/Main-Campus-Washington-DC/Res…> and submit a CV and cover letter listing the names and contact information of 2-3 references.* Review of applications will begin immediately and continue until the position is filled. Prospective applicants may email Dr. Bayet ( bayet(a)american.edu) with any questions. Apologies for cross-posting! *Essential Functions* - *Data Management:* Assisting with data collection in adherence with study protocols, such as: informed consent, EEG, fNIRS, and/or eye-tracking measurements, transferring research data files to the lab server. - *Participant Recruitment and Support:* Outreach, recruitment, and communication with families who participate in the research, such as: designing and implementing outreach/recruitment materials, assessing study eligibility, scheduling study visits, maintaining contact with participating families. - *Data Entry and Processing:* Conduct data entry, data pre-processing, video coding, and data management, in adherence with study protocols. - *Personnel:* Onboarding and supervision of undergraduate research assistants. - *Study General Support:* Assisting with designing and implementing experimental procedures, such as: creating and validating stimuli, surveys, and/or paradigms; monitoring materials and supplies. - *Compliance:* Develop and monitor IRB protocols for approval, modification, or renewal. - *Other duties as assigned by supervisor.* Opportunity to contribute to conference presentations and/or manuscript writing, if desired. Position Type/Expected Hours of Work: The initial position is for 1-year and is renewable contingent upon continued funding, a 6-month probationary period, and successful completion of duties. *Required Education and Experience:* - High school diploma or equivalent required. - 1-3 years' relevant experience, such as undergraduate research experience, is required. - Demonstrated interest in developmental psychology, cognitive science, and/or cognitive neuroscience required, such as from undergraduate coursework or research experience. - Excellent organizational and project management skills are required, including initiative, self-motivation, rigor, attention to details, ability to work independently on multiple tasks, ability to learn new skills in a fast-paced environment, and ability to meet deadlines. - Excellent communication and interpersonal skills are required, including comfort interacting professionally with families, infants, and undergraduate students, and ability to work effectively with people from diverse backgrounds. - Prior experience in developmental research (e.g., with infants/children) and/or human neuroimaging research (e.g., EEG, MEG, fNIRS) which may include undergraduate research experience (strongly preferred, but not strictly required if has some other relevant research experience). - Flexibility to adapt to changing hours, such as the ability to run study visits with families during weekends, or occasionally during the evening, is required. *Preferred Education and Experience:* - Bachelor's degree in Psychology or Neuroscience or closely related field preferred. - Computational skills and programming experience in Matlab, R, and/or Python preferred, but not strictly required. - Relevant experience with neuroscience/psychology research tools (e.g., NetStation, Psychtoolbox, Datavyu, Children Helping Science, EEGLAB, Homer, BIDS), data analysis, data processing, manuscript preparation, and/or social media or community outreach a plus. - The ability to start in or before January 2025 and the intention to make a 2-years commitment is strongly preferred. *Additional information:* The Developmental Cognitive Neuroscience Laboratory is part of the Neuroscience Department <https://www.american.edu/cas/neuroscience/> and the Center for Neuroscience and Behavior <https://www.american.edu/cas/center-neuroscience/> at American University. American University provides a stimulating intellectual environment, just 2 miles from downtown Washington DC. DC offers a vibrant research community, and American University enjoys proximity to other notable research institutions such as the National Institutes of Health. With extensive public transit, an exciting cultural and restaurant scene, many museums and public parks, and proximity to other green spaces in the surrounding region (e.g., Appalachian trail, Shenandoah National Park), Washington DC consistently ranks amongst the top US metropolitan areas for quality of life. *Benefits* AU offers a competitive benefits package including a 200% matching retirement plan, tuition benefits for full-time staff and their families, several leadership development certificates, and has been recognized by the American Heart Association as a fit-friendly worksite. Click here to learn about American University's unique benefit options <https://secure-web.cisco.com/1xOwxDSlkRlXlYPPZYWq0QpcjQRmrUewLamlS2mE8G0X9U…> . *Other Details* - Hiring offers for this position are contingent on successful completion of a background check. - Employees in staff positions at American University must deliver their services to the university from either the District of Columbia, Maryland, or Virginia, or perform work on-site at the university. - Please note this job announcement is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice. - American University is an E-Verify <https://secure-web.cisco.com/1XvV9ls4UAniSQMlhDR3Q7UDPXIx7GKNSsIF67po-xqKDS…> employer *Contact Us* For more information or assistance with the American University careers site, email theworkline(a)american.edu. *American University is an equal opportunity, affirmative action institution that operates in compliance with applicable laws and regulations. The university does not discriminate on the basis of race, color, national origin, religion, sex (including pregnancy), age, sexual orientation, disability, marital status, personal appearance, gender identity and expression, family responsibilities, political affiliation, source of income, veteran status, an individual’s genetic information or any other bases under federal or local laws (collectively "Protected Bases") in its programs and activities.*

Sept. 13, 2024

Link updated: UK PhD studentship opportunity

by Goodfellow, Marc

The University of Exeter, UK, is offering an EPSRC-funded PhD studentship in Neuroscience and Artificial Intelligence. This project is open to students with a background in Mathematics, Physics, Computer Sciences, or Natural Sciences, and an interest in Neuroscience. The successful candidate will use recent Neuroscience findings to make Deep Networks learn more sustainably, generalise better, be more resistant to injuries, and be more explainable. For information on the studentship and how to apply, please visit https://www.exeter.ac.uk/study/funding/award/?id=5228. The application deadline is midday on Friday 4th October 2024. For more information on this project see https://www.exeter.ac.uk/v8media/recruitmentsites/documents/Improving_Artif…

Sept. 12, 2024

UK PhD studentship opportunity

by Goodfellow, Marc

The University of Exeter, UK, is offering an EPSRC-funded PhD studentship in Neuroscience and Artificial Intelligence. This project is open to students with a background in Mathematics, Physics, Computer Sciences, or Natural Sciences, and an interest in Neuroscience. The successful candidate will use recent Neuroscience findings to make Deep Networks learn more sustainably, generalise better, be more resistant to injuries, and be more explainable. For information on the studentship and how to apply, please visit https://www.exeter.ac.uk/study/funding/award/?id=5228. The application deadline is midday on Friday 4th October 2024. For more information on this project see https://www.exeter.ac.uk/v8media/recruitmentsites/documents/Improving_Artif… ence_through_Neuroscience_(Dr_Joel_Tabak).pdf<https://www.exeter.ac.uk/v8media/recruitmentsites/documents/Improving_Artif…>

Sept. 12, 2024

Postdoc / PhD student for 3 years -- How to be flexible – organizing and optimizing task-dependent information processing in the visual system

by David Rotermund

The Computational Neurophysics lab at the University of Bremenheaded by Dr. Udo Ernst offers at the earliest date possible: *Postdoc / PhD student in Computational Neuroscience **for 3 years* In this project we want to study organization and optimization of flexible information processing in neural networks, with specific focus on the visual system. You will use network modelling,numerical simulation, and mathematical analysis to investigate fundamental aspects of flexible computation such as task-dependent coordination of multiple brain areas for efficient information processing, as well as the emergence of flexible circuits originating from learning schemes which simultaneously optimize for function and flexibility. These studies will be complemented by biophysically realistic modelling and data analysis in collaboration with experimental work. Here we will investigate selective attention as a central aspect of flexibility in the visual system, involving task-dependent coordination of multiple visual areas. ============ = Official text = ============ The Computational Neurophysics lab at the University of Bremenheaded by Dr. Udo Ernst offers at the earliest date possible: *Research Assistant / Postdoc in Computational Neuroscience (f/m/d)* German federal pay scale EG13 TV-L (100 %) *limited for 3 years*(according to § 2 WissZeitVG) *How to be flexible – organizing and optimizing task-dependent information processing in the visual system* In this project we want to study organization and optimization of flexible information processing in neural networks, with specific focus on the visual system. You will use * network modelling, * numerical simulation, * and mathematical analysis to investigate fundamental aspects of flexible computation such as task-dependent coordination of multiple brain areas for efficient information processing, as well as the emergence of flexible circuits originating from learning schemes which simultaneously optimize for function and flexibility. These studies will be complemented by biophysically realistic modelling and data analysis in collaboration with experimental work done in the lab of Prof. Dr. Andreas Kreiter, also at the University of Bremen. Here we will investigate selective attention as a central aspect of flexibility in the visual system, involving task-dependent coordination of multiple visual areas. * * *Requirements**:* Ideal candidates will have a completed academic university degree (Master’s/University Diploma) in computational neuroscience, physics, computer science or related fields. A doctorate in this field would be a positive addition to the application. There is the possibility of further qualification. Applicants must have a strong background in neural networks, dynamical systems, mathematics and/or data analysis, and experience in programming (we use Python in our lab). Above all, you must be highly motivated, responsible, have a strong desire to learn and be able to work proactively in an international research environment. Fluency in English (both written and spoken) is required. The Computational Neurophysics Lab offers a good working atmosphere, direct involvement in international research and attractive facilities. You will have the opportunity to link your research to a wide range of other topics being studied in our lab, such as collective dynamics in neural systems, information processing in deep spiking networks, and the development of visual cortex prostheses. *General hints:* Open to unconventional approaches in research and teaching, the University of Bremen has retained its character as a place of short distances for people and ideas since its founding in 1971. With a broad range of subjects, we combine exceptional performance and innovative potential. As an ambitious research university, we stand for research-based learning approaches and a pronounced interdisciplinary orientation. We actively pursue international scientific cooperation in a spirit of global partnership. Today, around 23,000 people learn, teach, research and work on our international campus. In research and teaching, administration and operations, we are firmly committed to the goals of sustainability, climate justice and climate neutrality. Our Bremen spirit is expressed in the courage to dare new things, in supportive cooperation, in respect and appreciation for each other. With our study and research profile and as part of the European YUFE network, we assume social responsibility in the region, in Europe and in the world. The University of Bremen is family-friendly, diverse and sees itself as an international university. We therefore welcome all applicants regardless of gender, nationality, ethnic and social origin, religion/belief, disability, age, sexual orientation and identity. As the University of Bremen intends to increase the proportion of female employees in science, women are particularly encouraged to apply. Disabled applicants will be given priority if their professional and personal qualifications are essentially the same. For questions of the research project please contact: Dr. Udo Ernst, E-Mail: _udo(a)neuro.uni-bremen.de_ For general information on this topic, see also: _https://www.uni-bremen.de/ernstlab <https://www.uni-bremen.de/ernstlab>_ _Detailed instructions for applicants_ Your application must comprise: *Motivation letter* Your 1–2-page essay should address the following questions: * What is your background? What areas have you worked in previously, and how do you think this will help you in this role? * What attracts you to computational neuroscience? * What computational neuroscience problem(s) are you most interested in? * What is your motivation for joining our project? * What are your plans for your future career? * When will you definitely be able to begin? *Curriculum Vitae* Send a tabular CV with your contact details, and all stages of education and employment. * * *List of skills, awards, publications* List your skills, especially language skills (including level of proficiency), that you think might be useful for the job. Also list any awards you have received and any peer-reviewed publications, if you have any. * * *Contact details of two academic references* One of the referees should be your PhD and/or MSc supervisor. Please inform your referees before listing their names so that they are not surprised when we contact them. You can apply in English or German, whichever language you are more comfortable with. Please explicitly address each of the specified requirements in your application (see detailed instructions below), and send your application documents until *07.10.2024*by indicating the *job id A007-24 to* Universität Bremen Institut für Theoretische Physik Frau Agnes Janssen Hochschulring 18 D-28359 Bremen or as one PDF file by unencrypted electronic mail to: _ajanssen(a)neuro.uni-bremen.de <mailto:ajanssen@neuro.uni-bremen.de>_. We kindly ask you to send us only copies (no portfolios) of your application documents, as we cannot return them. They will be destroyed after the selection process has been completed. Please note that incomplete applications will not be considered.

Sept. 11, 2024