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COSYNE 2023: Travel grants, Registration, Tutorials
by Tomas Hromadka 09 Dec '22

09 Dec '22

==================================================== Computational and Systems Neuroscience 2023 (Cosyne) MAIN MEETING 09 - 12 March 2023 Montreal WORKSHOPS 13 - 14 March 2023 Mont-Tremblant www.cosyne.org ==================================================== IMPORTANT DATES Registration is now open. Travel grants applications are now open. Travel grant application deadlines *31 December 2022, 11.59PM PST (Undergraduate Travel Grant)* 24 January 2023, 11.59PM PST (Other travel grants) ---------------------------------------------------- COSYNE MEETING & WORKSHOPS ---------------------------------------------------- The annual Cosyne meeting provides an inclusive forum for the exchange of empirical and theoretical approaches to problems in systems neuroscience, in order to understand how neural systems function. The MAIN MEETING is single-track. A set of invited talks is selected by the Executive Committee, and additional talks and posters are selected by the Program Committee, based on submitted abstracts. The WORKSHOPS feature in-depth discussion of current topics of interest, in a small group setting. Cosyne topics include but are not limited to: neural basis of behavior, sensory and motor systems, circuitry, learning, neural coding, natural scene statistics, dendritic computation, neural basis of persistent activity, nonlinear receptive field mapping, representations of time and sequence, reward systems, decision-making, synaptic plasticity, map formation and plasticity, population coding, attention, neuromodulation, and computation with spiking networks. ----------------------------------------------- TRAVEL GRANTS ----------------------------------------------- Applications are now open for travel grants to attend the conference. Each awardee will receive at least $500 to help offset the costs of travel, registration, and accommodations. Larger grants may be available to those traveling from outside North America. Special consideration is given to scientists who have not previously attended the meeting, under-represented minorities, students who are attending the meeting together with a mentor, undergraduate students, and authors of submitted Cosyne abstracts. We currently offer five travel grant programs for New Attendees, Presenters, Mentors, Undergraduates, and Childcare travel grants. For details on applying, see www.cosyne.org/travel-grants. ---------------------------------------------------- COSYNE TUTORIALS ---------------------------------------------------- Cosyne 2023 will host tutorial sessions on 09 March 2023. For details on Cosyne tutorials please visit www.cosyne.org/tutorials. Cosyne 2023 Tutorial Session Sponsored by the Simons Foundation Topic: Methods in Reinforcement Learning for Neuroscience Speaker: Kimberly Stachenfeld (DeepMind) Kimberly Stachenfeld is a Research Scientist at DeepMind. Her research spans topics in Computational Neuroscience and Machine Learning, and focuses on the general question of how to learn structured, expressive world models that enable flexible reasoning. In ML, she is specifically interested in methods and applications for learned forward models using graph neural networks, and in Neuroscience, she mainly works on mathematical models of hippocampal representations to efficient, scalable RL learning. Learn to Use the International Brain Laboratory (IBL) Brainwide Map Dataset Tutorial The IBL recently released a Brainwide Map of neural activity during decision-making! It consists of 547 Neuropixel recordings of 32784 neurons across 194 regions of the mouse brain, and we want to make it easy for you to use it to test your own hypotheses. At this tutorial we’ll teach you how to use our API, ONE, to search and download datasets, and will show you how to do basic analysis such as raster plots, single cell PSTHs, and brain region averages. INVITED SPEAKERS Demba Ba (Harvard University) Camilla Bellone (University of Geneva) Frans de Waal (Emory University) Tatiana Engel (Cold Spring Harbor Laboratory) Robert Froemke (New York University) Catherine Hartley (New York University) Sheena Josselyn (SickKids) Adam Kepecs (Washington University) Tim Lillicrap (DeepMind) Mackenzie Mathis (École Polytechnique Fédérale de Lausanne) Srdjan Ostojic (École Normale Supérieure) Anne-Marie Oswald (University of Chicago) Nathalie Rochefort (University of Edinburgh) Maryam Shanechi (University of Southern California) Kimberly Stachenfeld (DeepMind) ORGANIZING COMMITTEE General Chairs: Laura Busse (LMU Munich) and Tim Vogels (IST Austria) Program Chairs: Jessica Cardin (Yale) and Blake Richards (McGill) Workshop Chairs: Anna Schapiro (U Penn) and Andrew Saxe (Oxford) Tutorial Chair: Kanaka Rajan (Mount Sinai) DEIA Committee: Hysell Oviedo (CUNY) and Aman Saleem (UCL) Undergraduate Travel Chairs: Angela Langdon (Princeton) and Sashank Pisupati (Princeton) Fundraising Chair: Michael Long (NYU) Social Media Chair: Grace Lindsay (Columbia) Audio-Video Media Chair: Carlos Stein Brito (EPFL) Poster Design: Xaq Pitkow (Rice) PROGRAM COMMITTEE Jessica Cardin (Yale) Co-chair Blake Richards (McGill) Co-chair Yashar Ahmadian (Cambridge) Mark Andermann (Harvard) Omri Barak (Technion) Brice Bathellier (Paris) Yoram Burak (Hebrew University) Johannes Burge (U Penn) Chandramouli Chandrasekaran (Boston U) SueYeon Chung (Columbia) Jeremiah Cohen (Allen Inst) Anne Collins (Berkeley) Christine Constantinople (NYU) Carina Curto (Penn State) Jan Drugowitsch (Harvard) Tatiana Engel (CSHL) Sean Escola (Columbia) Annegret Falkner (Princeton) Kevin Franks (Duke) Rainer Friedrich (FMI Basel) Andrea Hasenstaub (UCSF) Monika Jadi (Yale) Santiago Jaramillo (U Oregon) Kohitij Kar (MIT) Narayanan Kasthuri (U Chicago) Jens Kremkow (Berlin) Guillaume Lajoie (MILA) Sukbin Lim (Shanghai) Scott Linderman (Stanford) Ashok Litwin-Kumar (Columbia) Mackenzie Mathis (EPFL) Paul Miller (Brandeis) Ida Momennejad (Microsoft) Eilif Muller (U Montreal) Marieke Mur (Western U) Kathy Nagel (NYU) Daniel O'Connor (Johns Hopkins) Hysell Oviedo (CUNY) Il Memming Park (Stony Brook) Joseph Paton (Champalimaud) Adrien Peyrache (McGill) Xaq Pitkow (Rice) Kanaka Rajan (Mount Sinai) Nathalie Rochefort (Edinburgh) Aman Saleem (UCL) Cristina Savin (NYU) Tatyana Sharpee (Salk) Aparna Suvrathan (McGill) Saori Tanaka (ATR) Daniela Vallentin (MPI Ornithology) Melissa Warden (Cornell) Brad Wyble (U Penn) Marta Zlatic (Cambridge) EXECUTIVE COMMITTEE Stephanie Palmer (U Chicago) Zachary Mainen (Champalimaud) Alexandre Pouget (U Geneva) Anthony Zador (CSHL) Anne-Marie Oswald (U Chicago) CONTACT meeting [at] cosyne.org COSYNE MAILING LISTS Please consider adding yourself to Cosyne mailing lists (groups) to receive email updates with various Cosyne-related information and join in helpful discussions. See www.cosyne.org/mailing-lists for details.

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Postdoctoral Swartz Fellowships in Computational Neuroscience at Yale
by Murray, John 09 Dec '22

09 Dec '22

Postdoctoral Swartz Fellowships in Theoretical and Computational Neuroscience at Yale University The Swartz Program for Theoretical Neuroscience at Yale University invites applications for up to two postdoctoral positions in Theoretical and Computational Neuroscience, with flexible start date in 2022. Competitive candidates include those with a strong quantitative background who wish to gain neuroscience research experience. We especially encourage candidates with an interest in collaborating directly with experimental neuroscientists. The candidates will be expected to perform theoretical/computational studies relevant to one or more laboratories affiliated with the Swartz Program at Yale (Jessica Cardin, Michael Crair, Damon Clark, Jonathan Demb, George Dragoi, Thierry Emonet, Michael Higley, Joe Howard, Monika Jadi, Jamie Jeanne, Alfred Kaye, Liang Liang, Benjamin Machta, John Murray, Anirvan Nandy, Ilker Yildririm, Steven Zucker). Applicants will be encouraged to participate in neuroscience and quantitative biology community at Yale, including through the Wu-Tsai Institute (https://wti.yale.edu/) and the Quantitative Biology Institute (https://qbio.yale.edu/) Candidates must hold a Ph.D. or equivalent degree by the time of beginning the fellowship. Please send a CV, selected (p)reprints, contact information for two or three references, and a statement of research interests including which laboratories at Yale are of interest. All application materials should be sent to the following e-mail address with "Swartz" in the email title: john.murray(a)yale.edu<mailto:john.murray@yale.edu>. Review of applications will begin January 7, 2023 and continue until positions is filled. For any questions, please contact John Murray. Yale University is an affirmative action/equal opportunity employer. Yale values diversity in its faculty, students, and staff and especially welcomes applications from women and underrepresented minorities. https://neurojobs.sfn.org/job/35847/postdoctoral-swartz-fellowship-position… John D. Murray ----------------------------------------------- Associate Professor of Psychiatry, Physics, and Neuroscience Wu Tsai Institute Yale University murraylab.org<https://murraylab.org/> -----------------------------------------------

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Post-Doctoral position in Cognitive and Sensorimotor Neuroscience on human gargalesis | Donders Institute
by Konstantina Kilteni 09 Dec '22

09 Dec '22

Dear colleagues, We are excited to announce an opening postdoctoral position at our new lab at Donders Institute for Brain, Cognition and Behaviour, to work on a starting ERC project on gargalesis (tickle) perception: https://cordis.europa.eu/project/id/101039152. The main research focus of the project concerns when, where, how and why we interpret a touch applied on our body as ‘ticklish’. To address these questions, we will combine robotic technology, somatosensory psychophysics, neuroimaging (fMRI with focus on MVPA), brain stimulation (TMS), and advanced statistical modelling techniques. Requirements: • You should hold a PhD in the field of Neuroscience, Psychology, Cognitive Science, Biomedical Sciences, Engineering, or a related field. • You have skills and documented experience in collecting and analysing psychophysical, physiological, and behavioural data, as well as in analysing fMRI data, including the use of MVPA methods. • You have experience with, or are interested in, statistical and computational modelling. • You have a passion for research on the interface between neuroimaging, psychology and cognitive science. • You are curious, ambitious, and are able to work independently. • You are a team player with strong communication and coordination skills. • You have excellent English language skills and academic writing skills. Candidates will contribute to all steps of the research from literature review to implementation of study design, data collection, data analysis and preparation of manuscripts. The position is available for 1 year with the possibility for continuation for 2 more years, starting soon after the application deadline (with some flexibility on the starting date). For further information, please follow the link: https://www.ru.nl/en/working-at/job-opportunities/postdoctoral-researcher-i… Deadline of applications: January 15th, 2023 Interviews: January 25th, 2023 We are very curious and very excited about our research. Join us!! Konstantina Kilteni, Ph.D. Assistant Professor Department of Neuroscience | Karolinska Institutet Solnavägen 9 | 17165 Stockholm | Sweden https://www.kiltenilab.org/ |https://ki.se/en/neuro/kilteni-laboratory När du skickar e-post till Karolinska Institutet (KI) innebär detta att KI kommer att behandla dina personuppgifter. Här finns information om hur KI behandlar personuppgifter<https://ki.se/medarbetare/integritetsskyddspolicy>. Sending email to Karolinska Institutet (KI) will result in KI processing your personal data. You can read more about KI’s processing of personal data here<https://ki.se/en/staff/data-protection-policy>.

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

09 Dec '22

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

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

09 Dec '22

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

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

08 Dec '22

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

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

07 Dec '22

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

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

07 Dec '22

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

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

07 Dec '22

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

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Postdoc on Brain network mechanisms underlying spatial cognition
by Peter Dayan 07 Dec '22

07 Dec '22

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

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