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Interdisciplinary PhD program in London, UK
by Silver, Angus Dec. 15, 2022

Dec. 15, 2022

Interdisciplinary PhD program in London, UK – call for 2023 applications – deadline 10th January. The London Interdisciplinary Biosciences Consortium (LIDo) Doctoral Training Partnership (DTP) is a BBSRC funded collaborative partnership offering world-class interdisciplinary research. LIDo unites an exciting team of outstanding universities and unique specialist institutions to provide innovative cutting-edge interdisciplinary research in the heart of one of the world's most vibrant and scientifically stimulating cities. LIDo will be offering 41 fully funded studentships in September 2023 across our DTP and iCASE routes of entry; these include home tuition fees and a tax-free stipend in the region of £19,668. A maximum of 11 of these positions can be offered to students eligible for overseas fee rates, where LIDo will cover the full fee amount. DTP Route In the first year of the programme DTP students will undertake two 4-month research projects in different partner institutions, selecting from a catalogue of over 200 topics. The choice of PhD topic is finalised after the second rotation project. Research opportunities are available across the breadth of BBSRC remit. Exemplar projects can be found on our website: https://www.lido-dtp.ac.uk/projects and DTP students will have the opportunity to contact potential supervisors in the Spring ahead of our call for projects. LIDo is particularly keen to welcome students from mathematics, computer science, engineering and the physical sciences who are eager to apply their skills and experience to biological problems and students from the plant sciences for exciting new projects available at our specialist academic and associate partners. All DTP students undertake a compulsory 3-month internship (PIPS) during their PhD to gain experience and context for careers where the transferable skills developed during their PhD programme can be usefully employed. iCASE Route Industrial collaborative (iCASE) students begin working on their named project from the start of the course. These projects represent genuine partnerships between academics within the LIDo consortium and industrial colleagues, allowing students to experience both distinctive environments in a mutually productive and supportive team and an extended placement of 3-18 months with their non-academic partner. Training and Cohort Building During the first-year, students will receive advanced training in fundamental and advanced mathematical, computational, and statistical skills for interdisciplinary and systems biology research. Expert in-house training in biological concepts and exposure to the history, trends and structure of the biotechnology and pharmaceutical industries make up the remaining first year teaching. Each year a week of cross research council remit teaching cushions the two rotations providing students the opportunity to hear from academic, industry, government, and not-for-profit speakers on a range of topics in the boundaries of BBSRC remit. The extraordinary LIDo teaching and research-intensive environment sits within a framework of robust and established cohort building activities, culminating each year in an academic retreat for the students. Application We enthusiastically invite applications by all highly motivated students from a wide range of academic backgrounds including biological, physical, computational, engineering or mathematical disciplines. Applicants must hold, or be expected to achieve, a first or high upper second-class honours degree (or equivalent), or an MSci or other Masters degree. For details on how to apply and the link to our online application form please go to: www.lido-dtp.ac.uk/apply<http://www.lido-dtp.ac.uk/apply> The application window will close on Tuesday 10th January 2023 at 5pm. R. Angus Silver, FRS Professor of Neuroscience and Wellcome Trust Principal Research Fellow Department of Neuroscience, Physiology and Pharmacology University College London Gower Street London WC1E 6BT Tel : 020 7679 7830 www.ucl.ac.uk/silverlab/

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Associate Research Scholar at Columbia University
by Michael Woodford Dec. 15, 2022

Dec. 15, 2022

*Position for Associate Research Scholar with the Cognitive and Behavioral Economics Initiative, Columbia University* The Cognitive and Behavioral Economics Initiative (CBEI) at Columbia University invites applications for an Associate Research Scholar (ARS) position to begin May 1, 2023 or later. The appointment will initially be for one year but is renewable based on satisfactory performance and availability of funding. The Associate Research Scholar will facilitate research on number cognition and the role of imprecise number representations as a source of errors and biases in economic decisions. A focus of the research will be the comparative evaluation of alternative quantitative models of the resource constraint that limits the precision of number representations, and the way in which these representations change depending on the statistics of the decision problems that are presented and, on the time allowed for mental processing. The Associate Research Scholar will conduct behavioral experiments, develop and test computational models of cognitive processes, and participate in data analysis and manuscript preparation, under the direction of Prof. Michael Woodford. *Qualifications* Applicants must have a Ph.D. in Economics, Neuroscience, Computer Science, Physics, or a related discipline, and at least three years of postdoctoral experience in related research. The ideal candidate will have strong computational skills, and experience conducting behavioral experiments, as well as superior motivation, drive, and demonstrated aptitude for research. Previous experience with interdisciplinary collaboration is strongly desired. For additional details and instructions for how to apply, see the job posting at https://academic.careers.columbia.edu/#!/108222.

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Spring School INTERDISCIPLINARY COLLEGE 2023: Invitation to Participate
by Herbert Jaeger Dec. 14, 2022

Dec. 14, 2022

The Interdisciplinary College (https://interdisciplinary-college.org/) is an annual one-week spring school, now in its 24th year. It offers a dense 4-track state-of-the-art course program in the wider sciences of intelligent/cognitive systems: Cognitive and Computational Neuroscience, Psychology, Machine Learning, AI and Philosophy. The perspective and mission is decidedly interdisciplinary. The 2023 event will take place in Guenne, Lake Moehne, Germany, on March 12-17, 2023 Chairs: Elisabeth Zimmermann, Gregor Schöner Each IK is centered on a *focus theme*. In 2023 the focus is on the role that physical interaction of an agent (with the environment, other agents, or its own body) plays for cognition. An offering of about 25 courses (each course 4-6 hours) is grouped under the perspectives of Movement & Bodily Experience; Neural Dynamics and Grounded Cognition; Experiencing Self and Others; Engaging with Technology & Things. The IK is also a unique social and networking event. Minds meet, music is played, and friends are made in long evening and night sessions in the welcoming conference site at Lake Moehne. While the IK has traditionally been mainly a European event, participants from outside Europe are highly welcome! Please visit https://interdisciplinary-college.org/ for the detailed program, venue and registration and everything else, including the IK's 40-year (pre-)history, and a totally seductive 6-min video on the startpage. --- Dr. Herbert Jaeger Professor of Computing in Cognitive Materials Rijksuniversiteit Groningen Faculty of Science and Engineering - CogniGron Bernoulliborg Nijenborgh 9, 9747 AG Groningen office: Bernoulliborg 402 phone: +31 (0) 631 921588 web: www.ai.rug.nl/minds/ -- Dr. Herbert Jaeger Professor of Computing in Cognitive Materials Rijksuniversiteit Groningen Faculty of Science and Engineering - CogniGron Bernoulliborg Nijenborgh 9, 9747 AG Groningen office: Bernoulliborg 402 phone: +31 (0) 631 921588 web: www.ai.rug.nl/minds/

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Computational Neuroscience PhD position - Newcastle, UK
by Andrej Bicanski Dec. 12, 2022

Dec. 12, 2022

Dear Colleagues, Please circulate this to any students that may be interested in a computational neuroscience PhD. The Topic: Modelling the staggered development and the decline with age of spatial coding in the mammalian brain + data analysis of single neuron recordings. In particular, the student will model the interactions between various spatial cells (head direction, place cells, etc) - e.g., in Matlab/Python. Candidates: This could be an interesting project for neuroscience/psychology graduates wanting to get into modelling. Students from outside these fields with a quantitative/programming background are welcome to apply too. Where: In sunny Newcastle, North UK, at Newcastle University, UK (with me), with a rotation in the lab of Prof. Colin Lever (Durham, UK, co-supervisor) Funding: Fully funded, for 4 years by the BBSRC. International and UK students can apply. Fees are covered! BBSRC Liverpool/Durham/Newcastle DTP3 scheme. Deadline: 9th of January Link: https://www.findaphd.com/phds/project/modelling-the-staggered-development-a…<https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.finda…> For more info on the application process visit the BBSRC DTP website: https://www.nld-dtp.org.uk/how-apply<https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.nld-d…> Happy to receive informal inquiries prior to application. Best wishes, Andrej Dr Andrej Bicanski School of Psychology & Biosciences Institute Faculty of Medical Sciences Newcastle University www.andrejbicanski.com

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COSYNE 2023: Travel grants, Registration, Tutorials
by Tomas Hromadka Dec. 9, 2022

Dec. 9, 2022

==================================================== 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 Dec. 9, 2022

Dec. 9, 2022

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 Dec. 9, 2022

Dec. 9, 2022

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 Dec. 9, 2022

Dec. 9, 2022

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 Dec. 9, 2022

Dec. 9, 2022

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 Dec. 8, 2022

Dec. 8, 2022

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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