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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 24, 2018