- Comp-neuro - lists.cnsorg.org

One postdoc and two PhD positions in Emmy-Noether group "Decision Neuroscience of Human Cooperation" in Hamburg, Germany

by Christoph Korn

Dear all, I would be very grateful, if you could circulate the following job announcements. One postdoc and two PhD positions are available within the newly funded Emmy-Noether research group "Decision Neuroscience of Human Cooperation" led by Christoph Korn. *Research topic and group:* The group's aim is to investigate the decision-making and learning processes relevant for successful social cooperation between humans. The planned projects rely on a variety of theoretical and methodological approaches including computational modeling of behavioral data, evolutionary game theory, model-based and multivariate analyses of fMRI data, pupillometry, virtual reality, and testing of psychiatric patients. The group is based at the Institute of Systems Neuroscience (head: Prof. Christian Büchel) at the University Medical Center Hamburg-Eppendorf in Hamburg, Germany. Psychiatric patients are tested in collaboration with Sabine Herpertz and her lab at the Heidelberg University Hospital. You can find more information here: http://christoph-korn.net/ *What the group offers:* - Opportunity to get hands-on supervision for learning various data acquisition and analysis techniques - Dynamic, interdisciplinary, and international research environment within the Institute of Systems Neuroscience - Research-dedicated T3 MR scanner (PRISMA), eye-tracking and VR laboratories, excellent infrastructure for behavioral testing - Multiple training opportunities within the institute (e.g., https://goo.gl/pU44vP) - Possibility to join the local graduate school, which is a member of national and international networks - Possibility of research stay with collaboration partners in the US *Your profile:* - You are interested in investigating how cooperation, decision-making, and learning relate to human brain activity and how they go awry in psychiatric disorders. - You like to design experiments, devise models, and analyze various types of data. - You have experience in conducting and analyzing behavioral experiments with human participants. - You are fluent in English. For the postdoc position and for one of the PhD positions, knowledge of German is not necessary. *Requirements for the postdoc position:* - A PhD (completed or close to the completion) in neuroscience, cognitive science, psychology, economics, medicine, or a related discipline. - Experience in conducting and analyzing neuroimaging experiments (including familiarity with SPM, FSL, or similar programs). - Experience in using programming languages such as Matlab, R, or Python. - Experience in writing and publishing peer reviewed scientific papers. *Requirements for the PhD positions:* - A Master of Science or an equivalent degree in neuroscience, cognitive science, psychology, economics, medicine, or a related discipline. - Experience in programming and in conducting or analyzing neuroimaging experiments is a big plus. - One of the PhD candidates will be (partly) based in Heidelberg to test psychiatric patients. This position is ideal for applicants with an interest in clinical psychiatry and requires knowledge of German to interact with patients. *Application and job specifications:* Applications will be accepted until the positions are filled. The first review of applications will be in the beginning of September 2018. Preferred starting date is January 2019 but later starting dates may be possible. Salary depends on experience and is based on German regulations (the postdoc position is remunerated with the factor 100%, the PhD positions with the factor 65%). The appointments will be initially for 3 years with the possibility for continuation. The group is committed to maintaining a diverse and inclusive environment. If you are interested, please send one pdf-document including your CV, a brief statement of research interest, and the contact details of two academic referees to *c.korn(a)uke.de <c.korn(a)uke.de>*. Informal inquiries are welcome. Looking forward to hearing from you, Christoph

Aug. 3, 2018

A biologically motivated and more powerful alternative to locality-sensitive hashing

by Rod Rinkus

I believe this community will be interested in a new downloadable Java app that I 've just made available on my web site (on this page <http://www.sparsey.com/CSA_explainer_app_page.html>), which describes an alternative, biologically motivated/plausible, way to achieve the goals of locality-sensitive hashing (LSH). This alternative model, called Sparsey, achieves a more graded notion of similarity preservation than LSH, and has many other advantages as well. Sparsey has a natural correspondence to the brain's cortex, centering on the idea that all items of information are stored as sparse distributed codes (SDCs), a.k.a., cell assemblies, in superposition in mesoscale cortical modules, e.g., macrocolumns (though other structures, e.g., mushroom bodies, are also candidates). Briefly, Sparsey preserves similarity from input space to SDR code space (measured as intersection size) as follows. - The process of choosing an SDC takes the form of Q independent softmax choices, one in each of the Q WTA competitive modules (CMs) that comprise the SDR coding field. - The familiarity (inverse novelty) of the input, denoted "G", which is in [0,1], is computed. This is an extremely simple computation. - The amount of noise in those Q softmax choice processes is modulated as a function of G. Basically, the softmax is over the distribution of input summations of the competing cells (in a given CM), but we use G to modulate (i.e. sharpen vs. flatten) those distributions. - When G is near 1 (perfect familiarity), the distributions are greatly sharpened, causing the expected number of CMs in which the cell with the highest input summation wins (and thus, the expected intersection of the resulting SDR with the closest matching previously stored SDR) to increase towards Q. When G is near 0 (completely novel), the distributions are flattened, causing the expected number of CMs in which the cell with max input summation wins (and thus, the expected intersection of the resulting SDR with the closest matching previously stored SDR) to decrease towards chance. In other words, this G-based modulation of the distributions, which can be viewed as varying the amount of noise in the choice process, achieves similarity preservation. I encourage members of this community to explore the app to understand this simple and more powerful alternative to LSH. I welcome your feedback. Sincerely, Rod Rinkus -- Gerard (Rod) Rinkus, PhD President, rod at neurithmicsystems dot com Neurithmic Systems LLC <http://sparsey.com> 275 Grove Street, Suite 2-400 Newton, MA 02466 617-997-6272 Visiting Scientist, Lisman Lab Volen Center for Complex Systems Brandeis University, Waltham, MA grinkus at brandeis dot edu http://people.brandeis.edu/~grinkus/ <http://people.brandeis.edu/%7Egrinkus/>

Aug. 2, 2018

Postdoc position in Geometric Methods for Deep and Reinforcement Learning at RIST

by Luigi Malagò

=========================================================== *Subject*: Postdoc position in Machine Learning (1 year, renewable up to 2 years) *Institution*: RIST - Romanian Institute of Science and Technology, Cluj-Napoca *Keywords*: Deep Learning, Reinforcement Learning, Stochastic Optimization, Optimization over Manifolds, Information Geometry, Riemannian Geometry *Application deadline*: 15 August 2018 (applicants are encouraged to apply earlier) *Salary*: around 2200 euro net *Official announcement*: http://rist.ro/en/details/news/postdoc-positio ns-in-deep-learning-and-machine-learning.html =========================================================== Dear colleagues, the Romanian Institute of Science and Technology (RIST) has an opening for a postdoc position, in the context of the DeepRiemann project “Riemannian Optimization Methods for Deep Learning”, funded by European structural funds through the Competitiveness Operational Program (POC 2014-2020). The appointments will be for 1 year, with possible extensions up to 2 years. The DeepRiemann project aims at the design and analysis of novel training algorithms for Neural Networks in Deep Learning, by applying notions of Riemannian optimization and differential geometry. The task of the training a Neural Network is studied by employing tools from Optimization over Manifolds and Information Geometry, by casting the learning process to an optimization problem defined over a statistical manifold, i.e., a set of probability distributions. The project is highly interdisciplinary, with competences spanning from Machine Learning to Optimization, Deep Learning, Statistics, and Differential Geometry. The objectives of the project are multiple and include both theoretical and applied research, together with industrial activities oriented to transfer knowledge, from the institute to a startup or spin-off of the research group. The positions will be part of the new Machine Learning and Optimization group https://rist.ro/en/teams.html, which performs research at the intersection of Machine Learning, Stochastic Optimization, Deep Learning, and Optimization over Manifolds, using geometric methods based on Information Geometry. The group is one of two newly-formed groups in Machine Learning at RIST. The official job announcement can be seen here: http://rist.ro/en/details/news/postdoc-positions-in-deep-lea rning-and-machine-learning.html Informal inquiries can be sent to Dr. Luigi Malagò <malago(a)rist.ro>, principal investigator of the DeepRiemann project. Application deadline: 15 August 2018 (applicants are encouraged to apply earlier) best regards, Luigi Malagò

Aug. 2, 2018

PhD positions at the Univ. of Leicester (for UK/EU candidates only)

by Okun, Michael (Dr.)

Fully Funded PhD Studentships (for UK/EU candidates only) to work at Prof. Quian Quiroga's lab at the Centre for Systems Neuroscience, University of Leicester, UK ( www.le.ac.uk/csn ). The Centre for Systems Neuroscience at the University of Leicester, UK, offers up to 2, 3-Year Fully Funded (stipend plus fees) PhD positions for UK/EU candidates, to study single cell recordings in humans – performed in epileptic patients for curative surgery. The project will investigate concept cells (a.k.a. Jennifer Aniston neurons) – that means, neurons in the hippocampus and surrounding areas that selectively fire to specific concepts, like different pictures and the written or spoken name of a particular person (e.g. Quian Quiroga et al, Nature 2005; Quian Quiroga Nature Reviews Neuroscience 2012), which are involved in declarative memory functions. The successful candidate will contribute to performing recordings with patients in collaborating hospitals and the analysis of the data to investigate the role of these neurons in memory formation. Candidates should have very good quantitative skills (data processing, and programing e.g. in Matlab) and a strong background or interest in neuroscience. They should be able to work both independently and as part of a research team within the Centre for System Neuroscience at Leicester and with our external collaborators. Informal enquiries are welcome and should be made to Emma Hawkins, Research Centre Manager, eeh18(a)le.ac.uk or 0116 252 3249. Interested candidates should send their curriculum vitae and a brief description of their scientific interests to Emma Hawkins (eeh18(a)le.ac.uk) The closing date for the applications is Friday 5th September. Interviews are anticipated to take place on the 12th September.

Aug. 2, 2018

CfP : Workshop on Continual Unsupervised Sensorimotor Learning, IEEE ICDL 2018

by Nguyen, Sao Mai

*2nd Call for Contributions* IEEE ICDL -2018 workshop on Continual Unsupervised Sensorimotor Learning 17th September 2018, Tokyo, Japan Website : http://conferences.au.dk/icdl-epirob-2018-workshop Participants are invited to submit short papers (max 4 pages) following the standard IEEE conference template. Selected contributions will be presented during the workshop as spotlight talks and in a poster session. Authors will be invited to submit extended versions of their papers for a special issue on Continual Unsupervised Sensorimotor Learning at IEEE TCDS. ================================================================== Scope As the algorithms for learning single tasks in restricted environments are improving, new challenges have gained relevance. They include multi-task learning, multimodal sensorimotor learning in open worlds and lifelong adaptation to injury, growth and ageing. In this workshop we will discuss the developmental processes involved in the emergence of representations of action and perception in humans and artificial agents in continual learning. These processes include action-perception cycle, active perception, continual sensory-motor learning, environmental-driven scaffolding, and intrinsic motivation. The discussion will be strongly motivated by behavioural and neural data. We hope to provide a discussion friendly environment to connect with research with similar interest regardless of their area of expertise which could include robotics, computer science, psychology, neuroscience, etc. We would also like to devise a roadmap or strategies to develop mathematical and computational models to improve robot performance and/or to attempt to unveil the underlying mechanisms that lead to continual adaptation to changing environment or embodiment and continual learning in open-ended environments. The primary list of topics covers the following (but not limited to): - Emergence of representations via continual interaction - Continual sensory-motor learning - Action-perception cycle - Active perception - Environmental-driven scaffolding - Intrinsic motivation - Neural substrates, neural circuits and neural plasticity - Human and animal behaviour experiments and models - Reinforcement learning and deep reinforcement learning for life-long learning - Multisensory robot learning - Multimodal sensorimotor learning - Affordance learning - Prediction learning Invited Speakers - Jochen Triesch, Frankfurt Institute of Advanced Studies, Germany - Emre Ugur, Boğaziçi University, Turkey (to be confirmed) - Yukie Nagai, Center for Information and Neural Networks, Japan (to be confirmed) - David Ha, Google Brain (to be confirmed) Call for Papers: Prospective participants in the workshop are required to submit a contribution as a short paper (max 4 pages) Submissions must be in PDF following the standard IEEE conference style <https://www.ieee.org/conferences/publishing/templates.html>. Send your PDF manuscript indicating [ICDL-EPIROB 2018] in the subject to: erhan.oztop(a)ozyegin.edu.tr Selected contributions will be presented during the workshop as spotlight talks and in a poster session. Contributors to the workshop will be encouraged to submit extended versions of the manuscripts to a special issue at IEEE Transactions on Cognitive and Developmental Systems (TCDS). Submissions will be peer reviewed consistent with the journal practices. Important Dates: Paper submission deadline: 5th August 2018 Notification of acceptance: 20th August 2018 Camera-ready version: 9th September 2018 Half-day workshop: 17th September 2018 Organizers: - Nicolás Navarro-Guerrero, Aarhus University, Aarhus, Denmark - Sao Mai Nguyen, IMT Atlantique, France - Erhan Öztop, Özyeğin University, Turkey - Junpei Zhong, National Institute of Advanced Industrial Science and Technology (AIST), Japan Nguyen Sao Mai nguyensmai(a)gmail.com Researcher in Cognitive Developmental Robotics http://nguyensmai.free.fr

July 31, 2018

[CFP] IROS-2018 Workshop: Towards Intelligent Social Robots: From Naive Robots to Robot Sapiens

by Amir Aly

CALL FOR PAPERS **Apologies for cross posting ** We are pleased to call for papers for the IROS-2018 workshop: "*Towards Intelligent Social Robots: From Naive Robots to Robot Sapiens*" In conjunction with the *IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)** - Madrid - Spain - October * *5th, 2018* *Webpage: **http://intelligent-social-robots-ws.com/* <http://intelligent-social-robots-ws.com/> *I. Aim and Scope *Robots that cook creatively, clean up our rooms dutifully, entertain our guests wittily and keep us company loyally. Robots that assist human users in their daily chores and provide support in times of need. Researchers around the world have envisioned such robot companions for a long time. Thanks to numerous innovations in sensor technology and software development, robots are now increasingly able to plan complex tasks in unknown environments, learn from experience and adapt to changes in the environment. The greatest challenges in robotics now lie in the development of robot skills and high-level AI-based functionalities that enable robots to work effectively in close collaboration with humans. Aside from the numerous technical challenges, which must be overcome before this vision can become a reality, multi-disciplinary research efforts are also invested into the social engineering of robots. In order to engineer “smart” robots that we accept, trust and welcome into our homes, it is paramount that we identify and investigate the factors that affect social interactions between humans and robots. For this purpose, computer scientists, AI researchers, engineers and psychologists tackle important questions that will determine whether robots will be perceived as helpful and reliable companions or as irritating nuisances. How should robots look, behave and communicate with us? What are our expectations of robot behavior in a social context? How can robots learn using the capabilities of their environments to achieve tasks and to address the needs of their human co-inhabitants? What kind of robot intelligence is required for what kind of tasks? In this workshop, participants will discuss with seasoned experts and young researchers what defines social and artificial intelligence for “smart” robots and how modern technological advances can equip robots with such intelligence. As such, this workshop aims to shed light on the intersection between cognitive science, artificial intelligence, and robotics research both from the theoretical and technical perspectives. Recent advances and possible avenues for future research in the field of “smart” robotics are principal topics of discussion during the workshop. ** *This workshop is endorsed by the IEEE Technical Committees*: *Human-Robot Interaction and Coordination, Cognitive Robotics, and Robot Learning*. *II. Keynote Speakers * 1. * Angelo Cangelosi *– University of Manchester/Plymouth – UK 2. *Yiannis Aloimonos *– University of Maryland – USA 3. * Selma Sabanovic *– Indiana University – USA 4. *Michael Beetz* – University of Bremen – Germany 5. *Matthias Scheutz *– Tufts University – USA *III. Submission * 1. For paper submission, use the following EasyChair web link: *Paper Submission <https://easychair.org/account/signin.cgi?key=75348348.9VXAN4Pe7LmBAKCx;time…>* . 2. Use the IEEE style (two-column format – US letter): *IEEE Templates <https://www.ieee.org/conferences/publishing/templates.html>*. 3. Submitted papers should be limited to 2-6 pages maximum. The primary list of topics covers the following points (but not limited to): - Multimodal human robot interaction - Cognitive modeling of human behavior - Cognitive architectures and strategies for intelligent interaction with the environment - AI and machine learning approaches applied to human-robot-environment interaction - Cloud robotics and ubiquitous computing - Ambient assisted living - Human intention recognition and prediction - Robot acceptance - Social engineering - Language learning, embodiment, and social intelligence - Computational modeling for high-level human cognitive functions - Predictive learning from sensorimotor information - Multimodal interaction and concept formulation - Language and action development - Learning, reasoning, and adaptation in collaborative human-robot tasks - Affordance learning - Learning by demonstration and imitation - Language and grammar induction in robots * IV. Important Dates * 1. Paper submission: *20-August-2018 * 2. Notification of acceptance: *30-August-2018* 3. Camera-ready version:* 7-September-2018 * 4. Workshop: *5-October-2018* *V. Organizers * 1. *Amir Aly *– Ritsumeikan University – Japan 2. *Sascha Griffiths *– Hamburg University – Germany 3. * Verena Nitsch *– Bundeswehr University – Germany 4. *Katerina Pastra* – Cognitive Systems Research Institute – Greece 5. *Tadahiro Taniguchi* – Ritsumeikan University – Japan ---------------------- *Amir Aly, Ph.D.* Senior Researcher Emergent Systems Laboratory College of Information Science and Engineering Ritsumeikan University 1-1-1 Noji Higashi, Kusatsu, Shiga 525-8577 Japan

July 31, 2018

3 Independent Academic Fellowship positions Computational Neuroscience

by Mark van Rossum

Academic Fellowship positions The University of Nottingham is a research intensive university ranked in the top 10 in the UK and in the top 30 of Europe. It has a strong tradition in Cognition, Perception, Mathematical Biology, and structural and functional Imaging. To support further development across these areas, and stimulate new research opportunities, the University has recently made a major investment in Computational Neuroscience. As part of this investment we are inviting applications for three independent fellowships (3 years). The positions are ideal for researchers with a strong vision that are planning to develop their own research group in a supportive, interdisciplinary environment with outstanding research facilities. We are interested in candidates working across a broad spectrum of research topics areas in Computational Neuroscience, including functional neuroimaging, neural networks, and models of cognition. Research methodologies could include numerical simulation, machine learning, theoretical neuroscience, and innovative data analysis. The Fellows will be based in the School of Psychology and/or Mathematical Sciences. For the online application form see https://www.nottingham.ac.uk/jobs/currentvacancies/ref/SCI219418 Informal inquiries: Prof Mark van Rossum, mark.vanrossum(a)nottingham.ac.uk, or Prof Mark Humphries, lpzmdh(a)exmail.nottingham.ac.uk. -- Mark van Rossum, Professor, Schools of Psychology and Maths, U Nottingham Psych Bldg Rm LG.19, 44-115-74 86851, 44-7722049644 This message and any attachment are intended solely for the addressee and may contain confidential information. If you have received this message in error, please contact the sender and delete the email and attachment. Any views or opinions expressed by the author of this email do not necessarily reflect the views of the University of Nottingham. Email communications with the University of Nottingham may be monitored where permitted by law.

July 31, 2018

CFP: Workshop on Crossmodal Learning for Intelligent Robotics in conjunction with IEEE/RSJ IROS 2018

by Pablo Barros

**Apologies for cross-posting** 1st CALL FOR PAPERS for the international workshop: * Crossmodal Learning for Intelligent Robotics * in conjunction with IEEE/RSJ IROS 2018 * Madrid, Spain - Friday 5 October 2018 * * Website: http://www.informatik.uni-hamburg.de/wtm/WorkshopCLIR18/index.php * I. Aim and Scope The ability to efficiently process crossmodal information is a key feature of the human brain that provides a robust perceptual experience and behavioural responses. Consequently, the processing and integration of multisensory information streams such as vision, audio, haptics and proprioception play a crucial role in the development of autonomous agents and cognitive robots, yielding an efficient interaction with the environment also under conditions of sensory uncertainty. Multisensory representations have been shown to improve performance in the research areas of human-robot interaction and sensory-driven motor behaviour. The perception, integration, and segregation of multisensory cues improve the capability to physically interact with objects and persons with higher levels of autonomy. However, the multisensory input must be represented and integrated in an appropriate way so that they result in a reliable perceptual experience aimed to trigger adequate behavioural responses. The interplay of multisensory representations can be used to solve stimulus-driven conflicts for executive control. Embodied agents can develop complex sensorimotor behaviour through the interaction with a crossmodal environment, leading to the development and evaluation of scenarios that better reflect the challenges faced by operating robots in the real world. This half-day workshop focuses on presenting and discussing new findings, theories, systems, and trends in crossmodal learning applied to neurocognitive robotics. The workshop will feature a list of invited speakers with outstanding expertise in crossmodal learning. II. Target Audience This workshop is open to doctoral students and senior researchers working in computer and cognitive science, psychology, neuroscience and related areas with the focus on crossmodal learning. III. Confirmed Speakers 1. * Yulia Sandamirskaya * Institute of Neuroinformatics (INI), University and ETH Zurich 2. * Angelo Cangelosi * Plymouth University and University of Manchester, UK 3. * Stefan Wermter * Hamburg University, Germany IV. Submission 1. Topics of interest: - New methods and applications for crossmodal processing (e.g., integrating vision, audio, haptics, proprioception) - Machine learning and neural networks for multisensory robot perception - Computational models of crossmodal attention and perception - Bio-inspired approaches for crossmodal learning - Crossmodal conflict resolution and executive control - Sensorimotor learning for autonomous agents and robots - Crossmodal learning for embodied and cognitive robots 2. For paper submission, use the following IEEE template: <http://ras.papercept.net/conferences/support/support.php>* 3. Submitted papers should be limited to *2 pages (extended abstract)* or *4 pages (short paper)*. 4. Send your pdf file to barros(a)informatik.uni-hamburg.de AND jirak(a)informatik.uni-hamburg.de Selected contributions will be presented during the workshop as spotlight talks and in a poster session. Contributors to the workshop will be invited to submit extended versions of the manuscripts to a special issue (to be arranged). Submissions will be peer reviewed consistent with the journal practices. V. Important Dates * Paper submission deadline: August 15, 2018 * Notification of acceptance: September 5, 2018 * Camera-ready version: September 15, 2018 * Workshop: Friday 5 October 2018 VI. Organizers * German I. Parisi * Hamburg University, Germany * Pablo Barros * Hamburg University, Germany * Doreen Jirak * Hamburg University, Germany * Jun Tani * Okinawa Institute of Science and Technology, Japan * Yoonsuck Choe * Samsung Research & Texas A&M University, TX, USA -- Dr.rer.nat. Pablo Barros Postdoctoral Research Associate - Crossmodal Learning Project (CML) Knowledge Technology Department of Informatics University of Hamburg Vogt-Koelln-Str. 30 22527 Hamburg, Germany Phone: +49 40 42883 2535 Fax: +49 40 42883 2515 barros at informatik.uni-hamburg.de https://www.inf.uni-hamburg.de/en/inst/ab/wtm/people/barros.html https://www.inf.uni-hamburg.de/en/inst/ab/wtm/

July 30, 2018

Four-year PhD in Computational Psychiatry at University College London

by Hrvoje Stojic

Four-year PhD in Computational Psychiatry at University College London The International Max Planck Research School on Computational Methods in Psychiatry and Ageing Research (https://www.mps-ucl-centre.mpg.de/en) seeks applicants for PhD fellowships to be based at University College London (UCL). The PhD programme is strongly interdisciplinary and invites applications from potential students with a broad range of backgrounds including, but not limited to, neuroscience, mathematics, statistics, machine learning, computer science, physics, psychology, and medicine. This is an international doctoral programme of the Max Planck UCL Centre for Computational Psychiatry and Ageing Research, which has sites in London and Berlin. The programme offers unique training in concepts and methods from computer science and statistics in relation to substantive research questions in cognitive neuroscience, psychiatry, and lifespan psychology. Training involves seminars, methods workshops, participation in summer schools, and collaboratively supervised research. Students will take one module per semester for the first two years of the programme on topics that range from psychiatry and decision science to advanced computational and statistical methods. The main focus of the London site is to address cognitive and theoretical neuroscience questions relevant to understanding psychiatric disorders. Methods include neuroimaging and pharmacology, computational modelling of behaviour (learning, decision-making, emotion), and large-scale smartphone- and internet-based data collection. Students will have a primary supervisor within the Centre and possible supervisors include Tobias Hauser (http://v1.tobiashauser.ch/) and Quentin Huys (https://quentinhuys.com/) Collaboration is encouraged within the Centre and with other UCL departments including the Wellcome Centre for Human Neuroimaging (https://www.fil.ion.ucl.ac.uk/) and Gatsby Computational Neuroscience Unit (http://www.gatsby.ucl.ac.uk/) We offer a generous four-year studentship stipend of £23,263 (tax free) per year, PhD registration fees at the current Home/EU rate, research expenses, and funds for travel to conferences or courses. (If you are an international student please note that this studentship only covers UK/EU fees and you will need to provide the difference between UK/EU and overseas fees.) Students will participate in international summer schools, seminars and workshops linked to the Berlin site, and have the opportunity to conduct a research project of up to 6 months in Berlin. Requirements: This is a highly competitive programme. Successful applicants should have, or expect to get, at least an upper 2nd class degree (or the foreign equivalent), and should have some familiarity with computational and statistical methods. Students wishing to undertake a PhD with Quentin Huys are expected to take and pass courses (http://www.gatsby.ucl.ac.uk/teaching/courses/index.html) at the Gatsby Computational Unit. The next intake of students will be October 2018 (with the possibility for a later start date). UCL is committed to employing more people with disabilities and especially encourages them to apply. UCL also seeks to increase the number of women in those areas where they are underrepresented and therefore explicitly encourages women to apply. Deadline: 26 August 2018. Shortlisted candidates will be interviewed in early September 2018 via Skype. HOW TO APPLY. Please send: 1) a CV, 2) a statement of why you want to do the PhD (no more than 1 page), 3) a copy of your strongest piece of academic work (e.g., thesis, publication). Please also arrange for two reference letters to be sent to us by referees. Your surname should be the first word in the subject line of these emails. The statement should indicate which of the named supervisors you would be most interested in having as a primary supervisor (multiple faculty can be listed as potential supervisors). Please ensure that your surname is the first word in the subject line of the email and that all documents are clearly labelled with your surname and the type of document. All documents and references should be sent to MaxPlanckPhD(a)ucl.ac.uk by 26 August 2018 at midnight. Questions about the programme can be directed to MaxPlanckPhD(a)ucl.ac.uk.

July 30, 2018

PhD Studentship, University College London, Centre for Medical Image Computing (CMIC)

by Andre Altmann

We are looking to fill a 4-year PhD studentship in the field of imaging genetics to work on drug resistant Epilepsy: Epilepsy is a group of neurological conditions that share the common characteristic of epileptic seizures. There are many types of epilepsy and many types of seizure. The diagnosis of epilepsy typically follows the occurrence of two or more seizures. While anyone can develop epilepsy at any point in life, it is most commonly diagnosed in children and people over 65 years of age. Currently, about 60 million people are suffering from epilepsy worldwide and over 500,000 in the UK alone. Anti-epileptic drugs (AED) are intended to reduce the frequency of seizures or even completely eliminate them. If AED treatment works, it allows people living with epilepsy to lead normal lives. However, in about one third of people none of the available drugs or combinations of drugs stop the seizures. These cases are considered treatment-resistant epilepsies and the underlying biology is still poorly understood. In this project, the successful candidate will help to advance knowledge about drug-resistant epilepsy. Using a large database of neuroimaging data from people with epilepsy, the first aim is to establish the imaging signature of drug-resistant epilepsy compared to drug-responsive epilepsy. That is, which brain regions show different cortical thickness or structural and functional connectivity changes in resistant vs responsive epilepsy? The second phase of the project involves an imaging-genetics approach to elucidate the genetic origin of drug-resistant epilepsy, which may help to identify drug targets for currently drug-resistant epilepsy. More information on requirements and the medical imaging CDT can be found here: http://medicalimaging-cdt.ucl.ac.uk/news/machine-learning-based-investigati… Kind regards, Andre

July 30, 2018

ANDA 2019 - G-Node Advanced Neural Data Analysis Course, April 1-18, 2019, Jülich, Germany

by Thomas Wachtler

ANDA 2019 - G-NODE ADVANCED NEURAL DATA ANALYSIS COURSE April 1 - 18, 2019 Haus Overbach, Juelich-Barmen, Germany Techniques to record neuronal data from populations of neurons are rapidly improving. Simultaneous recordings from hundreds of channels are possible while animals perform complex behavioral tasks. The analysis of such massive and complex data becomes increasingly challenging. This advanced course aims at providing deeper training in state-of-the-art analysis approaches in systems neuroscience. The course is addressed to excellent master and PhD students and young researchers who are interested in learning advanced techniques in data analytics and in getting hands-on experience in the analysis of electrophysiological data. Internationally renowned researchers will give lectures on statistical data analysis and data mining methods with accompanying exercises. Students will define and perform their own analyses on provided data to solve a challenge. Participants are required to have a strong interest in data analysis, a background in a mathematical or related field, knowledge of algebra, matrix operations, and statistics, and need to have solid programming experience (preferably in Python). FACULTY · Moshe Abeles, Bar-Ilan Univ, Israel · Izhar Bar Gad, Bar-Ilan Univ, Israel · Michael Denker, Juelich Research Center and RWTH Aachen Univ, Germany · Sonja Grün, Juelich Research Center and RWTH Aachen Univ, Germany · Björn Kampa, RWTH Aachen, Germany · Tatiana Korotkova, MPI and University of Cologne, Germany · Christian Machens, Champalimaud Centre for the Unknown, Portugal · Martin Nawrot, University of Cologne, Germany · Yifat Prut, Hebrew Univ Jerusalem, Israel · Alexa Riehle, CNRS, Marseille, France · Alexander Thiele, University of Newcastle, UK · Thomas Wachtler, G-Node, LMU Munich, Germany TOPICS COVERED Single neuron properties and statistics · Stochastic processes · Surrogate methods · Detection of spatio-temporal patterns · Unitary Events · Statistical analysis of massively parallel spike data · Higher-order correlation analyses · Spike-LFP relationship · Population coding · State space analysis · Machine learning · Data mining · Data management, reproducibility, data sharing · Elephant toolbox REQUIREMENTS Applicants should be familiar with linear algebra, probability, differential and integral calculus and experienced using Python or Matlab. Preparatory reading material will be provided. Students should bring their own laptops and should be able to install software on their system. Students that do not have a suitable laptop should indicate this immediately after acceptance to the course. We will be able to provide a small number of laptops for the time of the course. COURSE FEE A course fee of 1000 Euros will be charged to cover costs for accommodation and meals. Limited financial support may be available for students that otherwise would not be able to attend, which is to be indicated in the application. HOUSING Accommodation in 2-bed rooms for students will be provided at the course site. HOW TO APPLY The application should include · a letter of motivation (max 1 page) · curriculum vitae (please indicate the relevant courses you have taken) · description of programming experience · a letter of recommendation. Please send all documents as a single PDF file to <advanced-course(a)g-node.org>. APPLICATION DEADLINE Applications must be received by SEPTEMBER 30, 2018. Early application is encouraged. For further information see http://www.g-node.org/anda2019 ORGANIZERS · Sonja Grün, Juelich Research Center and RWTH Aachen Univ, Germany · Martin Nawrot, University of Cologne, Germany · Yifat Prut, Hebrew University Jerusalem, Israel · Thomas Wachtler, G-Node, Ludwig-Maximilians-Universität München, Germany

July 30, 2018

Call for participants – workshop on Computational Neuroscience and Robotics: Astrocyte-Neuron interactions, Spiking Neural Networks and Autonomous robotics. University of York, 3-5 Sep 2018.

by David Halliday

This 2.5 day workshop in the historic city of York is accepting applications for participation. We have invited speakers from USA, EU and UK. Due to sponsorship from EPSRC we can offer free registration for all participants. Free accommodation is available for PhD, early career researchers and workshop presenters. Travel bursaries for registered PhD students are also available. For an up to date list of speakers and details of how to register see the website: https://www.york.ac.uk/spanner-workshop We are still accepting abstracts for posters or contributed talks. Further details: https://www.york.ac.uk/spanner-workshop

July 30, 2018

Cognitive Computing - Merging Concepts with Hardware - Call for Abstracts: Deadline Approaching: July 31

by Prof. Dr. Gordon Pipa

- - - Call for Abstracts: Deadline Approaching: July 31 - - - COGNITIVE COMPUTING: MERGING CONCEPTS WITH HARDWARE December 18-20, 2018, Hannover, Germany http://www.cognitive-comp.org/ ** An interdisciplinary networking event / scientific conference ** We would like to draw your attention to a slightly unorthodox scientific community event that could be realized with the generous support from the Volkswagen Foundation, Germany’s largest private organization for the advancement of scientific research. The aim of this event is to work towards a general, productive, and rigorous theory of “computing” in non-digital, nonlinear physical substrates. Biological brains and unconventional computing machines would become understandable as different instantiations of the same underlying principles. Three scientific communities, namely • cognitive and computational neurosciences, • theory of computation, and • nonlinear materials, devices and systems have since long been exploring diverse facets of such principles of non-digital computing. But differences in terminology, discipline-specific objectives and a scattered spectrum of formal methods have handicapped cross-fertilization. Everything in this conference is geared toward stimulating linkages between these fields: • single-track with rather few, rather long oral presentations, • long break and poster session times for person-to-person talking, • keynote and plenary speakers of interdisciplinary renown, • a limited (200) number of participants, • a splendid setting in the Castle of Herrenhausen, a heritage of the Kings of Hannover, with adjoining hectares of classical French gardening. Invited speakers: • Kwabena Boahen, Stanford University • Joanna J. Bryson, Univ. of Bath and Princeton University • Chris Eliasmith, University of Waterloo • Edward A. Lee, UC Berkeley • Demetri Psaltis, EPFL Lausanne • Pieter Roelfsema, Vrije Universiteit Amsterdam & Netherlands Institute for Neuroscience • Susan Stepney, University of York • Ipke Wachsmuth, University of Bielefeld • David Wolpert, Santa Fe Institute We solicit the submission of 2-page abstracts, with themes oriented toward our five topical sessions: • applications of unconventional computing systems, • theoretical concepts and mathematical foundations, • neuromorphic hardware, • novel physical substrates, • guides from neuroscience for computing technologies, encouraging survey / introductory / didactic contributions (besides the standard discipline-specific result reports which are also possible). Detailed information can be found on http://www.cognitive-comp.org/ and in the Call for Abstracts that is posted there. Timelines: • Abstract submission: July 31 • Notification of acceptance: September 30 • Final abstract for online publication: October 31 Registration fees: • Students (incl. PhD students): 150 Euro • Others (academic): 300 Euro • Industry: 900 Euro Contributors of accepted oral presentations will be exempted from fees and will receive travel refunding. The organizers: • Daniel Brunner (photonics, neuromorphic architectures; University of Besançon) • Herbert Jaeger (machine learning, nonlinear dynamics; Jacobs University Bremen) • Stuart Parkin (nano systems, quantum electronic materials; Max-Planck-Institute for Microstructure Physics, Halle) • Gordon Pipa (neuroinformatics and cognitive computing; University of Osnabrück)

July 30, 2018

PhD Studentship, University of Osnabrueck- Research Training School on Computaional Cognition

by Prof. Dr. Gordon Pipa

We are looking for 9 PhD candidate for Research Training School funded by the DFG (German science foundation) on "Computational Cognition". The positions are to be filled by October 1, 2018 for a period of 3 years. More information: http://computational-cognition.eu/ https://www.uni-osnabrueck.de/universitaet/stellenangebote/stellenangebote_d etail/109_ikw_phd_candidates.html The RTG Computational Cognition aims at reintegrating Cognitive Science and Artificial Intelligence. PhD students of the RTG will be educated in both subjects in order to combine the findings of these fields and thus to get a better understanding of human and machine intelligence. Research fields involved in the RTG are Neuroinformatics, Neurobiopsychology, Bio-Inspired Computer Vision, Knowledge-Based Systems, Cognitive Natural Language Processing & Communication, Cognitive Modeling, Artificial Intelligence, Psycho/Neurolinguistics, Computational Linguistics and Cognitive Computing. The RTG will focus on the integration of two research fields and has a focus on machine learning, deep learning and dynamical systems, computer vision combined with experimental methods including EEG and Eye tracking. Detailed information on the core areas of the offered PhD projects can be obtained from the spokesmen of the RTG, Prof. Dr. Gordon Pipa (gpipa(a)uni-osnabrueck.de) and Prof. Dr. Peter König (pkoenig(a)uni-osnabrueck.de) The RTG will be incorporated into the Cognitive Science PhD program founded in 2002. PhD students of the RTG will take advantage of an interdisciplinary environment, which nevertheless focuses on a common research topic and offers a broad range of methodological synergies between the projects. Required Qualifications: Applicants are expected to have an academic degree (Master/Diploma), experience in at least one of the domains listed above, proven experience in interdisciplinary work as well as a good command of the English language. Osnabrück University has been certified as a family-friendly university committed to helping working/studying parents and carers balance their family and work life. The university aspires to ensure equal opportunities for men and women and strives to work towards a gender balance in schools or departments where new appointments are made. If equally qualified candidates apply, preference will be given to those with special needs. Applications with the usual documentation should be submitted by e-mail in a single PDF file to the director of the Institute of Cognitive Science, Prof. Dr. Kai-Uwe Kühnberger (kkuehnbe(a)uni-osnabrueck.de) with a cc to office(a)ikw.uni-osnabrueck.de no later than August 23, 2018.We will consider applicants who have: Best Gordon ---------------------------------------------------------------------------- ----------- Professor and Chair of the Neuroinformatics Department Dr. rer. nat. Gordon Pipa Institute of Cognitive Science, Room 50/218 University of Osnabrueck Wachsbleiche 27, 49090 Osnabrück, Germany tel. +49 (0) 541-969-2277 fax (private). +49 (0) 5405- 500 80 98 home office. +49 (0) 5405- 500 90 95 e-mail: gpipa(a)uos.de webpage: http://www.ni.uos.de research gate: https://www.researchgate.net/profile/Gordon_Pipa/?ev=prf_act linkedin: https://de.linkedin.com/in/gordon-pipa-47771539 Personal Assistent and Secretary of the Neuroinformatic lab: Anna Jungeilges Tel. +49 (0)541 969-2390 Fax +49 (0)541 969-2246 Email: anna.jungeilges(a)uni-osnabrueck.de visit us on http://www.facebook.com/CognitiveScienceOsnabruck https://twitter.com/#!/CogSciUOS

July 30, 2018

PhD position in Neuroscience available immediately (Italy / USA)

by Marco Tamietto

A new European Research Council (ERC) Consolidator grant starts at the University of Torino, Italy, for 5 years (~ 2 million euros). The grant “LIGHTUP – Turning the cortically blind brain to see” is awarded to prof. Marco Tamietto (www.marcotamietto.com) The project investigates the neural correlates of visual awareness and of non-conscious vision in patients with *blindsight* and in non-human primates (macaques) with V1 destruction. To this aim, a broad range of methods will be used, including 3T and 7T (f)MRI, neurophysiological recordings and brain stimulation (TMS). The project is embedded in an outstanding international and interdisciplinary context, including the University of Oxford (UK), Tilburg University (NL) and NIH (USA), with granted access to their excellent facilities. We offer a full-time PhD Student post for 4 years. Applications of highly motivated candidates with interests in systems neuroscience, vision sciences and neuroimaging are welcomed. The successful applicant will be appointed by the University of Torino, but he/she will be expected to spend a significant amount of time at the NIH in Bethesda (USA). In fact, the PhD student will be co-supervised by prof. M. Tamietto and prof. D. Leopold, and the position is specifically focused on behavioural and fMRI studies in non-human primates. For further information please visit http://www.marcotamietto.com or contact Prof. M. Tamietto (marco.tamietto(a)unito.it) or Prof. D. Leopold ( leopoldd(a)mail.nih.gov)

July 27, 2018

[Deadline Approaching] CfP: CI Methods in Processing and Analysis of Neuronal Big Data at BI 2018, Texas, Dec. 7-9.

by Mufti Mahmud

*[Apologies for cross posting.]* *Call for Paper for Special Session on* *Computationally Intelligent Methods in Processing and Analysis of Neuronal Big Data* *11th Brain Informatics Conference (BI 2018), Arlington, Texas, USA, December 7-9, 2018* *Web: http://uta.engineering/conferences/bi-2018/ <http://uta.engineering/conferences/bi-2018/>* Organizers: *Mufti Mahmud1, M Shamim Kaiser2, Ning Zhong3, Nitish V Thakor4* *1 **Computing and Technology, Nottingham Trent University, NG11 8NS – Nottingham, UK* 2*Institute of Information Technology, Jahangirnagar University, Savar, 1342 – Dhaka, Bangladesh* 3*Dept. of Life Science and Informatics, Maebashi Institute of Technology, 371-0816 - Maebashi-City, Japan* *4**Singapore Institute for Neurotechnology, National University of Singapore, 117456 – Singapore; &* *Dept. of Biomedical Engineering, Johns Hopkins University, Baltimore, 21205 – MD, USA* *Introduction:* The brain receives and processes information simultaneously coming from diverse sources. The neurons, being the basic information processing units, interconnect to each other to form hierarchical and/or parallel pathways. Technologies related to neural systems engineering have been employed to study these pathways along with processing and modelling of neuronal data for disease diagnosis and brain decoding purposes. Combining both experimental and computational approaches in recent years, thanks to the advancements in neurotechniques, scientists can access large amount of neuronal data and apply computationally intelligent and nature-inspired machine learning techniques including deep learning and reinforcement learning on those data to suggest next generation experimental design aiming to decipher brain’s information processing capabilities and diagnose its diseases. *Scope:* Developing data-intensive and intelligent tools, as well as sophisticated neurotechniques, to process and analyse the neuronal big data is one of the biggest challenges posed to today’s multidisciplinary brain science community. To share recent progress in decoding neuronal information processing, both in healthy and diseased brain, this special session aims to provide a forum for scientists from diverse disciplines including – computer, electrical, biomedical, and neuro engineering – who are looking for more relevant information in interpreting brain functions and diagnosing diseases using expert and computationally intelligent systems. This special session expects to attract papers on recent research progress in the area of intelligent computational tools and techniques in acquiring and processing neuronal big data. The focus areas include, but not limited to, the following: Ø Neural systems engineering and technology to study neural pathways; Ø Processing and modelling of neuronal data for disease diagnosis and brain decoding; Ø Bio-inspired methods for network analysis and pattern recognition in neural data; Ø Novel machine learning techniques for neuronal big data analysis; Ø Application of deep and reinforcement learning to neuronal big data analysis; Ø Computationally intelligent techniques for neuroscience applications; Ø Neuroinformatics (including cloud computing and real-time systems); Ø Cognitive science applications (learning, workload, decision making, etc.) and data analytics; Ø Computational and imaging methods for human brain connectome; and Ø Information analysis in human brain machine interface (invasive, noninvasive). *Submission of papers:* Submit Springer Lecture Notes in Computer Science (LNCS) complaint – 10 page – pdf paper to the Special Session following the steps below: Ø Prepare the paper as per the Springer LNCS template from: http://www.springer.com/us/computer-science/lncs/conference-proceedings-gui… Ø Visit https://wi-lab.com/cyberchair/2018/bi18/scripts/ws_submit.php?subarea=S Ø Select the link: Special session on Computationally Intelligent Methods in Processing and Analysis of Neuronal Big Data Ø Select the link Submit a New Paper (TYPE I Submission) Ø Provide paper details (i.e., Author(s), Paper Title, Abstract, Keywords, PDF file to upload). *Important dates:* Ø Paper submission deadline: *30 July 2018* Ø Decision notification: *30 August 2018* Ø Special Session date: *7 December 2018* Ø Conference dates: *8-9 December 2018*. With kindest regards, *Mufti Mahmud, PhD* | (Senior) Lecturer of Computing & Technology <https://www.ntu.ac.uk/sat/about/academic_teams/comp_tech.html> | School of Science & Technology <https://www.ntu.ac.uk/sat/> | Nottingham Trent University <https://www.ntu.ac.uk/> Office: ERD200 | Erasmus Darwin Building | Clifton Campus | NG11 8NS – Nottingham | United Kingdom Phone: +44 (0)115 84 83202 | Email: mufti.mahmud(a)ntu.ac.uk Meeting requests: https://doodle.com/mufti <http://orcid.org/0000-0002-2037-8348> http://orcid.org/0000-0002-2037-8348 https://scholar.google.com/citations?user=L8em2YoAAAAJ&hl=en https://sites.google.com/site/muftimahmud/ https://www.ntu.ac.uk/staff-profiles/science-technology/mufti-mahmud Senior Member, IEEE <https://www.ieee.org/> & ACM <https://www.acm.org/> Associate Editor, IEEE Access <http://ieeeaccess.ieee.org/> Editorial Board Member, Cognitive Computation <https://www.springer.com/biomed/neuroscience/journal/12559> & Big Data Analytics <https://bdataanalytics.biomedcentral.com/> Student consultation hours: Drop-in sessions on Thursdays between 11.00 am and 12.30 pm. Appointments for a different time can also be arranged through email.

July 24, 2018

Postdoc in Computational and Mathematical Neuroscience (closing 29 July; EPSRC funded)

by James Rankin

**closes soon*, on 29 July* *Postdoctoral Research Fellow in Computational and Mathematical Neuroscience* Location: College of Engineering, Mathematics, Physical Sciences at the University of Exeter (Streatham Campus) Job reference: P62935 Application closing date: *29/07/2018* Interview date: *10/08/2018* Salary From £34,520 on Grade F, dependent on knowledge, skills and experience This new full-time post is available from *1st October 2018* on a fixed term contract basis for *2 years*. The College of Engineering, Mathematics and Physical Sciences, wishes to recruit a Postdoctoral Research Fellow to participate in the project Neural oscillator network modelling of auditory stream segregation. This EPSRC funded post is available from 01/10/2018 for 2 years. The successful candidate will join the Systems Biomedicine and Dynamical Systems research groups housed in the recently launched GBP 50m Living Systems Institute at the University of Exeter. These groups house over 50 researchers applying mathematical and computation approaches to study problems in neuroscience, biology and healthcare. The project will benefit from input from colleagues with expertise in neural networks, bifurcation theory, coupled oscillators and numerical methods. The Post: The project will involve developing mathematical and computational models to deepen our understanding of auditory stream segregation. This is a fundamental process in the auditory system that allows us to separate out and focus on distinct sound streams (e.g. voices) in a dynamic noisy environment. This process involves competition in order to resolve different interpretations of a given environment (e.g. different groupings of objects). Many aspects of this process are still not well understood, such as where in the brain segregation of streams is achieved, how the streams are encoded and the driving neural mechanisms. This project will develop a biologically motivated model inspired by a broad cross section of modelling and experimental literature (from anatomical, neurophysiological, brain imaging and behavioural experiments). The models developed will be based on networks of coupled neural oscillators. Neural oscillations are understood to be vital for the encoding of temporal information in auditory streaming. Dynamical systems theory including bifurcation analysis and numerical methods will provide the necessary tools to understand the dynamics of the models developed. About you: - Candidates with quantitative backgrounds (Mathematics, Physics, Engineering) and from Neuroscience programmes with a strong computational component are encouraged to apply. - Applicants will possess a PhD or equivalent in one of these areas or a related field. T - You will also be able to work collaboratively and supervise the work of others. - Programming experience in a high-level language (e.g. Matlab, Python, C/C++) is a must and knowledge of dynamical systems theory is a plus. - Experience working on interdisciplinary projects involving the application of mathematical and computational tools to problems in Biology or Neuroscience will be viewed favourably. The University offers some fantastic benefits including 41 days leave per year, options for flexible working, numerous discounts at leading retailers, onsite gym, cycle to work scheme, sector leading policies around maternity, adoption and shared parental leave (up to 26 weeks full pay), paternity leave (up to 6 weeks full pay), and a new Fertility Treatment Policy; and a stunning campus environment in the heart of Exeter. If you are not currently in Exeter please have a look at our website for some further information on what a beautiful part of the country we are based in. *For further information, please contact Dr James Rankin, email j.a.rankin(a)exeter.ac.uk <j.a.rankin(a)exeter.ac.uk>* https://jobs.exeter.ac.uk/hrpr_webrecruitment/wrd/run/ETREC1 07GF.open?VACANCY_ID=258266M3V7&WVID=3817591jNg http://emps.exeter.ac.uk/mathematics/staff/jar226 The University of Exeter is an equal opportunity employer. We are officially recognised as a Disability Confident employer and an Athena Swan accredited institution. Whilst all applicants will be judged on merit alone, we particularly welcome applications from groups currently underrepresented in the workforce.

July 24, 2018

IMBIZO DEADLINE TOMORROW: IBRO Simons Computational Neuroscience Imbizo 2019

by Tim Vogels

Dear all, I’d like to remind you that the deadline for next year's IBRO-Simons computational neuroscience imbizo is TOMORROW Tell your friends, and tell your students, especially your African students, as we are still lacking a proper pipeline to disseminate this information. The Imbizo is a summer school in computational neuroscience and machine learning, hosted January 6th - 27th 2019 in Cape Town, South Africa. We are generously sponsored by the International Brain Research Organisation (IBRO) and the Simons Foundation (Simons). TO APPLY visit https://imbizo.africa <https://imbizo.africa/> IF YOU ARE NOT SURE WHETHER YOU CAN AFFORD IT, BY ALL MEANS, APPLY. We have generous merit-based awards and stipends to give away!! The Imbizo is designed to introduce students with backgrounds in analytic fields (computer science, statistics, physics, mathematics, engineering, etc.) to the field of computational neuroscience. It will also benefit advanced experimental biologists who would like to learn more computational skills. It also provides an opportunity for students already working in computational neuroscience to do 3 weeks of intensive, focused work in a different sub-topic of the field. Students should generally be at Masters/early PhD level, and have completed at least a 2nd-year university level course in computer science, statistics, physics or mathematics. Some coding experience will also be helpful. More advanced level students (post-Docs, early career PIs) may also be accepted if they can motivate how the courses at the Imbizo could help their career. Well motivated, exceptional undergraduates will also be considered. African students are especially encouraged to apply. The faculty for 2019 include: Dora Angelaki (Bayor College, Houston) Demba Ba (Harvard Uni, Boston) Sophie Denève (ENS, Paris) Adrienne Fairhall (Univ of Washington, Seattle) Peter Latham (Univ College London) Timothy Lillicrap (Google Deepmind, London) Joseph Raimondo (Univ of Cape Town) Athanassia Papoutsi (IMBB-FORTH, Hellas) Srikanth Ramaswami (EPFL, Lausanne) Blake Richards (Univ Toronto) Andrew Trevelyan (Newcastle Univ., Newcastle) Misha Tsodyks (Weizmann Inst., Rehovot) Tim Vogels (Oxford) Byron Yu (Carnegie Mellon Univ, Pittsburgh) TO APPLY visit https://imbizo.africa <https://imbizo.africa/> "Imbizo" is an isiXhosa word, meaning "A gathering to share knowledge". The aim of the isiCNI is exactly this: to create an environment in which young African and international students can explore computational neuroscience together, forming strong friendships in the process. Three weeks of intensive lectures, tutorials, projects and fun! Who should apply? The Imbizo is designed to introduce students with backgrounds in analytic fields (computer science, statistics, physics, mathematics, engineering, etc.) to the field of computational neuroscience. It will also benefit advanced experimental biologists who would like to learn more computational skills. It also provides an opportunity for students already working in computational neuroscience to do 3 weeks of intensive, focused work in a different sub-topic of the field. Students should generally be at Masters/early PhD level, and have completed at least a 2nd-year university level course in computer science, statistics, physics or mathematics. Some coding experience will also be helpful. More advanced level students (post-Docs, early career PIs) may also be accepted if they can motivate how the courses at the Imbizo could help their career. Well motivated, exceptional undergraduates will also be considered. African students are especially encouraged to apply. What does it cost? The attendance fee for the isiCNI2019 is EUR 1,100.00. Thanks to our generous sponsors, significant bursaries are available to subsidise and waiver student fees, and provide some travel bursaries. Funding will be allocated according to need and merit. Please be sure to complete the relevant section of the application. IF YOU ARE NOT SURE WHETHER YOU CAN AFFORD IT, BY ALL MEANS, APPLY. We have generous merit-based awards and stipends to give away!!

July 23, 2018

Invitation to Participate in Software Engineering Practices in Cognitive Modelling and Computational Neuroscience Survey

by Furkan Kurtaran

Dear All, As a part of Master's thesis research, I am conducting an online survey on software engineering practices and problems in developing cognitive and neuroscientific architectures/frameworks/simulators and computational models on those platforms. If you have been involved in developing such cognitive/neuroscientific modelling tools and computational models on them, we will be grateful if you could answer our survey questions in the link given below: http://moodle.atilim.edu.tr/anket/index.php?r=survey/index&sid=579941&lang=… [1] The participation is voluntary and anonymous; the survey will take about 10 minutes. We hope to better understand and develop suggestions for improving cognitive modelling and computational neuroscience software from a software engineering point of view at the end of our research. As a symbol of gratitude of your participation, participants who complete the survey will be eligible for a prize draw for a $40 book check from Amazon. Best Regards, -- Furkan Kurtaran Computer Engineering Department Research Assistant Atilim University https://www.atilim.edu.tr/en/compe/page/1595/academic-staff Links: ------ [1] http://moodle.atilim.edu.tr/anket/index.php?r=survey/index&sid=579941&a…

July 23, 2018

Software Development Position -- University of Tübingen

by Andrea Burgalossi

A position as 'Data Analyst & Software Developer' is immediately available in the Burgalossi lab (www.burgalossilab.com) He/she will work closely with neuroscientists for developing software for the analysis of electrophysiological data and animal behavior (rodents). Specific tasks will also involve programming virtual-reality and/or video-tracking hardware, and developing software for the detection and scoring of animal behaviors. A strong quantitative background (e.g. degree in statistics, computer science, physics, mathematics, engineering, etc.) and excellent programming skills (e.g. MATLAB) are necessary. Background in neuroscience and experience in methods for neural data analysis are a plus. Candidates at various levels of academic degree (BSc, MSc, PhD) will be considered for this position. Applications should contain CV and names of at least two referees. Please send your application (or informal inquiries) electronically to Andrea Burgalossi (andrea.burgalossi(a)cin.uni-tuebingen.de) -- Andrea Burgalossi, PhD Cellular and Synaptic Basis of Behaviour Werner Reichardt Centre for Integrative Neuroscience (CIN) Otfried-Müller-Straße 25 72076 Tübingen Tel: +49-(0)7071-29-88797 Fax: +49-(0)7071-29-25006 Lab web: burgalossilab.com CIN web: http://www.cin.uni-tuebingen.de

July 18, 2018

HFSP postdoc in limbo, and perhaps at ENS

by Alessandro Treves

A postdoc is sought to join a HFSP-funded project to study analog cortical computations in linguistic processes. A collaboration with Naama Friedmann (TAU) and Remi Monasson (ENS) which includes, at SISSA, Sara Andreetta and several PhD students. Ideal candidates are interested in language but have expertise in mathematical approaches to neural computation - complementary to Sara's in behaviour. A fruitful interaction with Remi and his group may lead to a period based in Paris. Applications to be submitted by August 6, 2018, as indicated in https://www.sissa.it/bandi/selezione-pubblica-titoli-conferimento-di-n-1-as… (note: by 1pm!) with starting date Oct 1st. Inquiries at ale(a)sissa.it -- Alessandro Treves http://people.sissa.it/~ale/limbo.html SISSA - Cognitive Neuroscience, via Bonomea 265, 34136 Trieste, Italy +39-040-3787623 Ambassador (BlaBlaCar) +39-349-2504602

July 16, 2018

Postdoc positions on Consciousness Research at Monash Uni, Australia

by Naotsugu Tsuchiya

Position A: DP180100396 (in collaboration with Masafumi Oizumi, Hiroto Kawasaki, Giulio Tononi) No report paradigm in EEG/MEG/intracranial recordings and the analysis of integrated information across sensory and prefrontal cortex Position B: DP180104128 (in collaboration with Marta Garrido, Ueli Rutishauser, Ralph Adolphs) The analysis of MEG/intracranial recordings, using Granger causality and integrated information We are looking for highly talented postdocs (application from PhD students with a prospect of getting PhD in 1 year are welcomed) for the above two ARC-funded positions. Ideal candidates in both positions would have strong publications, strong programming skills in Matlab/Python, strong background in data analysis, preferably neuroimaging data or neural spikes. The projects include 1) design of various psychophysical paradigms (*pdf <https://academic.oup.com/nc/article/doi/10.1093/nc/niw023/2970153/Are-we-un…>)*, including no-report paradigms (*pdf <https://drive.google.com/file/d/0B9N0ysU85rs7bEF5d1VVX3J4T3c/view>*), which can be used for subsequent EEG/MEG/intracranial recording experiments and 2) analysis of EEG/MEG/intracranial data using the approximations of integrated information (link1 <http://www.eneuro.org/content/4/5/ENEURO.0085-17.2017>, *link <https://drive.google.com/open?id=0B9N0ysU85rs7NFVSQlIza215eVU> *, *link <http://www.pnas.org/content/early/2016/12/02/1603583113.abstract>*, *link <http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.10046…>)* ). Please send the inquiry with your CV to naotsugu.tsuchiya(a)monash.edu. Applicants with most fit background and skills will be contacted for subsequent interview over the internet. The positions will be available until they are filled. Regards Nao Tsuchiya -- -- *Nao (Naotsugu) Tsuchiya* Associate Professor *Monash Institute of Cognitive and Clinical Neurosciences* Attention and Memory Program School of Psychological Sciences Monash University 770 Blackburn Monash Brain Imaging facility, Clayton, VIC 3800 Australia T: +61 3 9905 4564 E: naotsugu.tsuchiya(a)monash.edu W: homepage: http://users.monash.edu.au/~naotsugt/Tsuchiya_Labs_Homepage http://med.monash.edu.au/psych/email-sig/miccn-email-sig.jpg <http://www.monash.edu/neuro-institute/> 2. Visiting Researcher at Department of Dynamic Brain Imaging, Advanced Telecommunications Research (ATR), Japan 3. Visiting Researcher at CiNet, Osaka University, Japan orcid.org/0000-0003-4216-8701

July 15, 2018

Postdoctoral / Research Specialist position in Neural Circuits and Behavior @ Janelia (USA)

by Reiser, Michael

Postdoctoral / Research Specialist position in Neural Circuits and Behavior https://www.janelia.org/lab/reiser-lab/positions The Reiser lab at the Janelia Research Campus seeks a creative scientist to join our endeavor to understand how the fly brain uses visual information to control behavior. We use behavioral, anatomical, imaging, electrophysiological, and computational techniques to crack the neural circuits for vision and navigation in Drosophila. This is an exciting time to be working on the fly brain. It is the golden age of Drosophila neuroanatomy—full brain connectomes and precise genetic access to nearly every cell type in the brain are on the horizon. It is likely that within the next few years the behavioral methods used for establishing functional roles for identified cell types will become rate limiting. We have developed a number of new instruments and methods for high-content behavioral analysis and are recruiting a scientist to help with the development and application of these new tools. In this position you would lead our efforts to apply these new tools to deeply map behavioral circuits. Many specific projects are possible that are related to active research topics in the lab (visual motion guided behaviors; visual place learning; central modulation of visual circuits). Requirements: - A keen interest in figuring out the brain. - Ph.D. in neuroscience, experimental biology, or a quantitative field. - Familiarity with diverse computing environments. - Experience in animal behavior, neuroanatomy, neurophysiology, instrumentation, computer vision, machine learning, and/or computational neuroscience is a big plus. Janelia is a unique, exciting research environment near Washington, D.C., with abundant opportunities for collaboration and learning new things. Interested applicants should apply by email; please include your curriculum vitae and research interests and arrange for three letters of reference to be sent to reiserm at janelia.hhmi.org. The Reiser lab is committed to maintaining a diverse and inclusive environment. Members of groups underrepresented in science are especially encouraged to apply. HHMI is an equal opportunity employer.

July 15, 2018

Open Ph.D. position on whole-brain calcium imaging at Technical University of Munich

by Gil Westmeyer

We are currently looking for a Ph.D. Student interested in functionally dissecting whole-brain calcium imaging data with cellular resolution obtained from zebrafish larvae undergoing systematic perturbations of neuronal activity. Our laboratory (westmeyerlab.org) at the School of Medicine of Technical University of Munich (https://www.tum.de/nc/en/homepage/) and The Institute for Biological and Medical Imaging (IBMI) http://www.helmholtz-muenchen.de/en/ibmi/ focuses on biological engineering of molecular sensors and actuators for neurobehavioral imaging. We have built a molecular imaging pipeline consisting of state-of-the-art fluorescent imaging techniques including neurobehavioral methods to simultaneously image behavior and brain activity in freely behaving animals (see for example NeuBtracker.org) We complement these dataset with exoeriments conducted by Light Sheet Microscopy and Light Field microscopy to obtain imaging volumes with high temporal sampling and confocal / 2-photon microscopy. We also capture calcium signaling from adult zebrafish and rodent brains using combined acquisitions with optoacoustic tomography or MRI. For our inter-disciplinary work, we are actively collaborating within Europe and in particular also with MIT and Caltech. If you are interested in computational analyses of whole-brain calcium imaging data, please visit westmeyerlab.org and submit a brief statement of your research interests and your CV to Gil Westmeyer.

July 14, 2018

Postdoctoral positions in Rinberg and Shoham labs

by Rinberg, Dmitry

The Rinberg and Shoham labs at NYU Medical School are seeking to fill multiple postdoctoral positions at the interface of computational systems neuroscience and advanced neurotechnology. The goal of our studies is to elucidate how sensory information is represented in the brain, and how the brain extracts information relevant for behavior. We are using rodent olfaction as a model system, and employing multiple modern techniques including one- and two-photon imaging and patterned optogenetics, Si-probe electrophysiology, and psychophysics approaches. In addition to conventional tools, we are developing new cutting edge optical, opto-acoustic and computational tools for bidirectional neural interfacing and applying these tools towards high-precision probing and monitoring of information processing in behaving animals. The postdoctoral researches will be involved in joint and individual lab projects. This is an excellent opportunity for computationally and technologically inclined candidates to find their niche in-between developing cutting edge technologies and applying the technologies to fundamental scientific questions. Our labs are part of NYU’s vibrant world-class hub for computational systems neuroscience, and of NYU Tech4Health, a new biomedical technology development institute. An ideal candidate should have a background in neuroscience, physics/engineering and math. Knowledge and experience in optics, imaging, multi-neuron physiology and computational methods are a big plus. Please contact Dima Rinberg: rinberg(a)nyu.edu<mailto:rinberg@nyu.edu> or Shy Shoham: shoham(a)nyu.edu<mailto:shoham@nyu.edu> See also: www.rinberglab.com<http://www.rinberglab.com>, niel.net.technion.ac.il<http://niel.net.technion.ac.il> ------------------------------------------------------------ This email message, including any attachments, is for the sole use of the intended recipient(s) and may contain information that is proprietary, confidential, and exempt from disclosure under applicable law. Any unauthorized review, use, disclosure, or distribution is prohibited. If you have received this email in error please notify the sender by return email and delete the original message. Please note, the recipient should check this email and any attachments for the presence of viruses. The organization accepts no liability for any damage caused by any virus transmitted by this email. =================================

July 12, 2018