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LM2017 - Second Call for Papers, Satellite Events and Sponsors (7 weeks until submission deadline)
by INFO CSNETWORK, Bústia Compartida Jan. 22, 2017

Jan. 22, 2017

**Apologies for crossposting** 2nd Call for Papers, Satellite Events and Sponsors Living Machines VI: The 6th International Conference on Biomimetic and Biohybrid Systems 25 – 28 July 2017 http://livingmachinesconference.eu/ <http://livingmachinesconference.eu/2017> Living Machines Conference | Home livingmachinesconference.eu Stanford will host Living Machines 2017! The 6th International Conference on Biomimetics and Biohybrid Systems will be hosted at Stanford University, California, US. To be hosted at Stanford University, Stanford, CA, USA Accepted papers will be published in Springer Lecturer Notes in Artificial Intelligence Submission deadline: March 10th, 2017 ______________________________________________________________ ABOUT LIVING MACHINES 2017 https://www.youtube.com/watch?v=WqPOCDh1FNw YouTube www.youtube.com and share it all with friends, family, and the world on YouTube. The development of future real-world technologies will depend strongly on our understanding and harnessing of the principles underlying living systems and the flow of communication signals between living and artificial systems. Biomimetics is the development of novel technologies through the distillation of principles from the study of biological systems. The investigation of biomimetic systems can serve two complementary goals. First, a suitably designed and configured biomimetic artefact can be used to test theories about the natural system of interest. Second, biomimetic technologies can provide useful, elegant and efficient solutions to unsolved challenges in science and engineering. Biohybrid systems are formed by combining at least one biological component—an existing living system—and at least one artificial, newly-engineered component. By passing information in one or both directions, such a system forms a new hybrid bio-artificial entity. The theme of the conference also encompasses biomimetic methods for manufacture, repair and recycling inspired by natural processes such as reproduction, digestion, morphogenesis and metamorphosis. The following are some examples of “Living Machines” as featured at past conferences: • Biomimetic robots and their component technologies (sensors, actuators, processors) that can intelligently interact with their environments. • Biomimetic computers—neuromimetic emulations of the physiological basis for intelligent behaviour. • Active biomimetic materials and structures that self-organize and self-repair. • Nature-inspired designs and manufacturing processes. • Biohybrid brain-machine interfaces and neural implants. • Artificial organs and body-parts including sensory organ-chip hybrids and intelligent prostheses. • Organism-level biohybrids such as robot-animal or robot-human systems. ACTIVITIES The main conference will take the form of a three-day single-track oral and poster presentation programme, 26th to 28th July 2017, hosted at Stanford University, California, USA. The conference programme will include five plenary lectures from leading international researchers in biomimetic and biohybrid systems, and the demonstrations of state-of-the-art living machine technologies. The full conference will be preceded by up to two days of Satellite Events hosted at Stanford University. SUBMITTING TO LIVING MACHINES 2017 We invite both full papers and extended abstracts in areas related to the conference themes. All contributions will be refereed and accepted papers will appear in the Living Machines Proceedings, published in the Springer-Verlag Lecture Notes in Artificial Intelligence. Full papers (minimum 8 pages, up to 12 pages) are invited from researchers at any stage in their career and should present significant findings and advances in biomimetic or biohybrid research. More preliminary work is better suited for short paper submission (minimum 4 pages, with a maximum of ten references and no more than three self-citations). Full papers will be accepted for either oral presentation (single track) or poster presentation with a short podium preview. Extended abstracts will be accepted for poster presentation only. Authors of the best full papers will be invited to submitted extended versions of their paper for publication in a special issue of the Taylor & Francis journal Connection Science. Satellite events Active researchers in biomimetic and biohybrid systems are invited to propose topics for full or half-day tutorials, symposia or workshops on related themes to be held on the 25th July at Stanford University. Attendance at satellite events will attract a small fee intended to cover the costs of the meeting. There is flexibility about the content, organisation, and budgeting for these events. Please contact us if you are interested in organising a satellite event! EXPECTED DEADLINES March 10th, 2017 Paper submission deadline April 28th, 2017 Notification of acceptance May 15th, 2017 Camera ready copy July 25th - 28th 2017 Conference SPONSORSHIP Organisations wishing to sponsor the conference in any way and gain the corresponding benefits by promoting themselves and their products through conference publications, conference events, and conference publicity are encouraged to contact the organisers to discuss the terms of sponsorship and necessary arrangements. We offer a number of attractive options to potential sponsors: http://livingmachinesconference.eu/about/ VENUE Living Machines 2017 will be hosted at Stanford University a world leading research University that this year celebrates its 125th anniversary. Stanford is located in California's Bay Area, one of the most intellectually dynamic and culturally diverse areas of the US. Organising Committee: Mark Cutkosky, Stanford University (Local Organizing Chair) Paul Verschure, Universitat Pompeu Fabra (Co-Chair) Tony Prescott, University of Sheffield (Co-chair) Michael Mangan, University of Lincoln (Programme Chair) Marc Desmulliez, Heriott Watt University, Scotland (Steering Committee) Anna Mura, Universitat Pompeu Fabra (Web and Communications) Nathan Lepora, University of Bristol (Communications)

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New JETCAS Special Issue: Low-Power, Adaptive Neuromorphic Systems: Devices, Circuit, Architectures and Algorithms
by Arindam Basu Jan. 21, 2017

Jan. 21, 2017

Dear all ** Apologies for cross-posting Would like to draw your attention to a new Special issue in JETCAS on "Low-Power, Adaptive Neuromorphic Systems: Devices, Circuit, Architectures and Algorithms" that I am co-editing with colleagues. Manuscript submission deadline is on April 30, 2017. Look forward to receiving your contributions. IEEE JOURNAL ON EMERGING AND SELECTED TOPICS IN CIRCUITS AND SYSTEMS CALL for PAPERS Low-Power, Adaptive Neuromorphic Systems: Devices, Circuit, Architectures and Algorithms Guest Editors Full name Email Affiliation Arindam Basu* arindam.basu(a)ntu.edu.sg Nanyang Technological University Tanay Karnik tanay.karnik(a)intel.com Intel Hai Li hai.li(a)duke.edu Duke University Elisabetta Chicca chicca(a)cit-ec.uni-bielefeld.de Bielefeld University Meng-Fan Chang mfchang(a)mx.nthu.edu.tw National Tsing Hua University Jae-sun Seo jaesun.seo(a)asu.edu Arizona State University (* Corresponding) Scope and Purpose The recent success of “Deep neural networks” (DNN) has renewed interest in bio-inspired machine learning algorithms. DNN refers to neural networks with multiple layers (typically two or more) where the neurons are interconnected using tunable weights. Though these architectures are not new, availability of lots of data, huge computing power and new training techniques (such as unsupervised initialization, use of rectified linear units as the neuronal nonlinearity, regularization using dropout or sparsity, etc.) to prevent the networks from over-fitting have led to its great success in recent times. DNN has been applied to a variety of fields such as object or face recognition in images, word recognition in speech or even natural language processing and the success stories of DNN keep on increasing every day. However, the common training method in deep learning, such as back propagation, tunes the weights of neural networks based on the gradient of the error function, which requires a known output value for every input. It would be difficult to use such supervised learning methods to train and adapt to real-time sensory input data that are mostly unlabeled. In addition, training and classification phases of deep neural networks are typically separated, such that training occurs in the cloud or high-end graphics processing units, while their weights or synapses are fixed during deployment for classification. However, this makes it difficult for the neural network to continuously adapt to input or environment changes in real-world applications. By adopting unsupervised and semi-supervised learning rules found in biological nervous systems, we anticipate to enable adaptive neuromorphic systems for many real-time applications with a large amount of unlabeled data, similar to how humans analyze and associate sensory input data. Energy-efficient hardware implementation of these adaptive neuromorphic systems is particularly challenging due to intensive computation, memory, and communication that are necessary for online, real-time learning and classification. Cross-layer innovations on algorithms, architectures, circuits, and devices are required to enable adaptive intelligence especially on embedded systems with severe power and area constraints. Topics of Interest This special issue invites submissions relating to all aspects of adaptive neuromorphic systems across algorithms, devices, circuits, and architectures. Possible scalability to human brain-scale computing level with energy-efficient online learning is desired. Submissions are welcome in the following topics or other related topics: · Spin mode adaptive neuromorphics with devices such as spin transfer nano-oscillator, domain wall memory, tunneling magnetic resistance, inverse spin hall effect, etc. · Memristive technology based learning synapse and neurons · Neuromorphic implementations of synaptic plasticity, short-term adaptation and homeostatic mechanisms · Self-learning synapses (STDP and variants) and self-adaptive neuromorphic systems · High fan-in scalable interconnect fabric technologies mimicking brain-scale networks · Circuits and systems for efficient interfacing with post-CMOS memory based learning synapses · Design methodology and design tools for adaptive neuromorphic systems with post-CMOS devices · Algorithm, device, circuit, and architecture co-design for energy-efficient adaptive neuromorphic hardware Important Dates 1. Manuscript submissions due: April 30, 2017 2. First decision: July 15, 2017 3. Revised manuscripts due: August 15, 2017 4. Final Decision: October 15, 2017 5. Final manuscripts due: November 15, 2017 Request for Information Arindam Basu (arindam.basu(a)ntu.edu.sg<mailto:arindam.basu@ntu.edu.sg>) https://mc.manuscriptcentral.com/jetcas Best regards, Arindam ________________________________ CONFIDENTIALITY: This email is intended solely for the person(s) named and may be confidential and/or privileged. If you are not the intended recipient, please delete it, notify us and do not copy, use, or disclose its contents. Towards a sustainable earth: Print only when necessary. Thank you.

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ICMNS 2017: *Reminder, Abstracts Due Jan 31, 2017*
by Zachary Kilpatrick Jan. 20, 2017

Jan. 20, 2017

This is a reminder that Abstract Submissions are due January 31, 2017 for the 3rd International Conference on Mathematical Neuroscience (ICMNS 2017), to be held at the Hotel Boulderado in Boulder, Colorado from May 30 to June 2, 2017. https://www.math.uh.edu/~zpkilpat/icmns2017/index.html <https://www.math.uh.edu/~zpkilpat/icmns2017/index.html> Meeting registration will open soon. Early Registration (Until March 31) will be $250 for students/postdocs, $350 for faculty, and $50 for tutorials. The International Conference on Mathematical Neuroscience will provide a forum for researchers to discuss current mathematical innovations emerging in neuroscience. A major aim of the conference is to attract and train young researchers on current methods in mathematical neuroscience. Abstract Submission: We encourage abstract submission by researchers from all areas of mathematical neuroscience. One page abstracts will be reviewed by a Program Committee and divided into three parallel talk sessions and a poster session. Details are given here: https://www.math.uh.edu/~zpkilpat/icmns2017/submissions.html <https://www.math.uh.edu/~zpkilpat/icmns2017/submissions.html> Student Travel Awards: This year, we will offer student travel awards, due to the generous support from NSF, SIAM, Burroughs Wellcome, and the University of Colorado. To apply, students must submit an abstract and include a current CV as part of their submitted document in Easychair. Confirmed Speakers Danielle Bassett (University of Pennsylvania) Paul Bressloff (University of Utah) Nicolas Brunel (University of Chicago) Sophie Deneve (École Normale Supérieure) Brent Doiron (University of Pittsburgh) Marla Feller (University of California, Berkeley) Ila Fiete (University of Texas) Stefano Fusi (Columbia University) Peter Thomas (Case Western Reserve University) Taro Toyoizumi (Riken Brain Science Institute) Tutorial Speakers: Paul Bressloff, Sophie Deneve, Brent Doiron, Stefano Fusi, Joel Zylberberg (University of Colorado, School of Medicine) Program Committee https://www.math.uh.edu/~zpkilpat/icmns2017/committees.html <https://www.math.uh.edu/~zpkilpat/icmns2017/committees.html> We hope to see you in Boulder this May! All the best Zachary Kilpatrick (University of Colorado) Julijana Gjorgjieva (Max Planck Institute for Brain Research) Robert Rosenbaum (University of Notre Dame)

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Fruit Fly Brain Hackathon 2017
by Yiyin Zhou Jan. 19, 2017

Jan. 19, 2017

Fruit Fly Brain Hackathon 2017 FFBH 2017 <http://www.bionet.ee.columbia.edu/hackathons/ffbh/2017>March 12, 2017Columbia University, New York, NY 10027 We are pleased to announce the 2nd Fruit Fly Brain Hackathon (FFBO 2017). This hackathon will feature the Fruit Fly Brain Observatory (FFBO) and its key components NeuroNLP and NeuroGFX. The former allows for exploring fruit fly brain data using plain English queries, and the latter facilitates the modeling and execution of such brain circuits. Brief tutorials will be given on the usage of the FFBO as well as developing new tools/features in FFBO. The hackathon is aimed at three main groups of participants: neurobiologists, modelers and software engineers. The goal of the hackathon is to bring together these three groups of participants to create new ideas to develop, use and improve the FFBO platform towards developing executable model of the fruit fly brain. The Fruit Fly Brain Hackathon is organized in conjunction with the Columbia Workshop on Brain Circuit, Memory and Computation on March 13-14, 2017. Participants of the hackathon are welcome to attend the workshop. Registration is free but all participants have to register <https://ffbo17.eventbrite.com/> (*https://ffbo17.eventbrite.com/ <https://ffbo17.eventbrite.com/>*). Organizers: Paul Richmond, Department of Computer Science, University of Sheffield Adam Tomkins, Department of Automatic Control and Systems Engineering, University of Sheffield Nikul Ukani, Department of Electrical Engineering, Columbia University Chung-Heng Yeh, Department of Electrical Engineering, Columbia University Yiyin Zhou, Department of Electrical Engineering, Columbia University More information can be found on the hackathon website: http://www.bionet.ee.columbia.edu/hackathons/ffbh/2017 ------------------------------------------------------------ ------------------ Best Regards, Yiyin Zhou, on behalf of the organizers

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Postdoc in Medical Data Science
by Philipp Berens Jan. 19, 2017

Jan. 19, 2017

The lab of Philipp Berens (www.berenslab.org) at the Institute for Ophthalmic Research (www.eye-tuebingen.de) at the Eberhard-Karls-University Tübingen is offering a position as Postdoctoral Researcher in _Medical Data Science for Ophthalmology_ to be filled as soon as possible, with funding for up to 4 years. The successful candidate will perform research at the interface of data science and medicine with the goal to advance statistical methods for predicting disease onset or identifying risk factors by combining classical epidemiological approaches with recent developments in deep learning. The work will be done in close collaboration with the lab of Marius Ueffing and the ZEISS Vision Lab at the Institute for Ophthalmic Research and will contribute to a better understanding of ophthalmic diseases such as diabetic retinopathy or macular degeneration. The Berens lab conducts research in computational neuroscience, data science and biostatistics with a focus on developing tools to integrate various data sources. We have recently developed a framework based on deep neural networks for detecting diabetic retinopathy from fundus images modeling the decision uncertainty of the classifier (https://doi.org/10.1101/084210) Tübingen is home to a vibrant machine learning community with ample opportunity for interaction with researchers at both the University as well as the Max Planck Institute for Intelligent Systems. The Institute of Ophthalmic Research is part of the Center of Ophthalmology, covering various aspects of ophthalmic research from basic retinal neuroscience to the development of gene therapy and neuroprosthetics. We offer employment with a salary and social benefits based on the collective agreement for public service employees in the academic and science sector, TV-L. The Eberhard-Karls-University of Tübingen promotes gender equality and therefore particularly encourages female scientists to apply. Preferential status will be given to handicapped persons, if equally qualified. Requirements: • PhD in machine learning, statistics or related fields • Experience with medical data • Programming experience in Python and R • Strong publication record and scientific independence Interested applicants should contact Dr. Philipp Berens (philipp.berens(a)uni-tuebingen.de) providing a curriculum vitae, a one-page description of past research experience & future research interests, a one-page description of the motivation for applying to this position and names of at least two people that could provide letters of reference. Please compile your application in one single PDF-file and add [Data Science Postdoc] to the subject line. -- University of Tübingen Institute for Ophthalmic Research http://www.berenslab.org NEW PHONE NUMBER: +49-7071-2988833

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3 years funded PhD in oscillatory behaviour in Alzheimer’s disease to establish biomarkers, Deadline 31st of January
by Eirini Mavritsaki Jan. 19, 2017

Jan. 19, 2017

Dear all, We are advertising a 3 year funded PhD project in "Investigating oscillatory behaviour in Alzheimer’s disease to establish biomarkers: an EEG and computational modelling programme of PhD study" Successful applicants for our funded PhD studentships will receive a tax-free research stipend that tracks UK Research Council rates (currently £14,296) and a fee waiver to the value of Home / EU student PhD fees (currently £4,120). Closing date for applications Tuesday 31 January 2017 at 23:59. This is a transdisciplinary STEAM Project This proposed PhD work follows high profile research by the University of Birmingham team (Prof. Kim Shapiro, Prof. Howard Bowman and Mr Ali Mazaheri). The project is collaborative work between Birmingham City University (Dr Eirini Mavritsak) and University of Birmingham (Prof. Kim Shapiro and Prof. Howard Bowman). The University of Birmingham team has access to ERP data of a semantic anomaly and word repetition task (Olichney et al, 2002). In the original analysis of the data Olichney and colleagues, the N400 component was analysed, which is related to semantic manipulation. Olichney and colleagues found evidence of N400 abnormalities in mild cognitive impairment patients, which predicted later progression to Alzhemier’s. We plan to simulate this data and the changes observed in this data by developing a computational model that is based on the sSoTS (Mavritsaki, Heinke, Humphreys and Deco, 2011) model. The synaptic currents that sSoTS contains will allow us to extract the ERP profile and simulate the above described experiment. In addition to that sSoTS model has already successfully simulated visual search outcomes for patients with Alzheimer’s (Mavritsaki and Humphreys, 2013). The project is separated into two phases: in phase 1, we plan to develop the computational model to simulate controls and mild cognitive impairment patients and in phase 2 we are planning to extend the model to allow us to predict the development of the disease based on identified biomarkers. The successful applicant will join the Centre for Applied Psychological Research (CAP Research) within the Department of Psychology at Birmingham City University. CAP Research is part of a vibrant and rapidly expanding research community, which offers applicants with an excellent opportunity to develop their research career. The applicant has the opportunity to have teaching experience, to participate in research seminars and to co-supervise undergraduate projects. The successful candidate will also be expected to attend the weekly meetings of the University of Birmingham research team. You can find further details on studying for a PhD and details of how to apply on the following link http://www.bcu.ac.uk/courses/social-sciences Candidate Qualification and Specifications: Essential Ø The applicant should hold a good undergraduate honours degree (First or 2:1) in psychology or related area. Ø The applicant should have experience of computational modelling, evidenced by previous work or masters degree. Ø A demonstrated understanding of research methods is essential (as evidenced by degree transcript grades for research methods and dissertation modules). Ø Experience in C++ and Matlab. Desirable Ø A Masters’ degree in research methods, psychology or computational modelling Ø Experience in EEG analysis Contact: Eirini Mavritsaki, Ph.D., CPsychol Email: eirini.mavritsaki(a)bcu.ac.uk<mailto:eirini.mavritsaki@bcu.ac.uk> Best regards, Eirini Mavritsaki ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Eirini Mavritsaki, PhD, CPsychol Senior Lecturer in Cognitive Psychology Director of Research in the School of Social Sciences Department of Psychology Faculty of Business Law and Social Sciences Birmingham City University The Curzon Building 4 Cardigan Street Birmingham B4 7BD eirini.mavritsaki(a)bcu.ac.uk<mailto:eirini.mavritsaki@bcu.ac.uk> 0121 331 6361 Special Issue in Frontiers 'Neuropsychology through the lenses of computational modelling' http://fron.tiers.in/go/r2e3M4 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

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Postdoctoral fellowship in computational neuroscience at Harvard
by Jan Drugowitsch Jan. 18, 2017

Jan. 18, 2017

Dear all, Jan Drugowitsch (Department of Neurobiology, Harvard) and Sam Gershman (Department of Psychology, Harvard) are seeking a postdoctoral fellow to work on a project combining computational modeling, psychophysics, and clinical studies. The project focuses on the neural basis of visual structure discovery, using motion perception as a model system. Our goal is to understand how neural circuits represent and reason about complex combinatorial structures, and how these neural circuits break down in autism. The postdoctoral fellow's main focus is the computational modeling component of the project. The Drugowitsch and Gershman labs are located in the Longwood medical area and Harvard’s Cambridge campus, respectively. Harvard, and the Boston area in general, has an excellent neuroscience community and programs in engineering, statistics, and related fields. Candidates must have a Ph.D. in a quantitative discipline and strong background in Bayesian modeling and computational neuroscience. Experience with visual psychophysics experiments is desirable but not essential. Applicants should send a CV and statement of research interests to Jan Drugowitsch (Jan_Drugowitsch(a)hms.harvard.edu) The initial appointment is for one year with the expectation of extension given satisfactory performance. Applications will be reviewed until the position is filled. Jan Drugowitsch will be attending the the Computational and Systems Neuroscience meeting on February 23-28 to interview potential candidates. Best regards, Jan Drugowitsch Assistant Professor in Neurobiology Harvard Medical School

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Excellence workshop ''Dynamical Network States, Criticality and Cortical Function'' (March 25-28, 2017 in Germany)
by David Rotermund Jan. 18, 2017

Jan. 18, 2017

We would like to invite you to participate in our excellence workshop “Dynamical Network States, Criticality and Cortical Function”. It will take place March 25-28, 2017 at the Hanse-Wissenschaftskolleg in Delmenhorst (near Bremen, Germany). Please feel free to forward the following information to anyone who you think may be interested in attending our workshop. Confirmed Speakers John Beggs, Matthias Bethge, Stefan Bornholdt, Mauro Copelli, Lucilla de Arcangelis, Thilo Gross, Michael Herrmann, Anna Levina, Klaus Linkenkaer-Hansen, Paolo Massobrio, Ruben Moreno-Bote, Eilif Benjamin Müller, Dietmar Plenz, Viola Priesemann, Silvia Scarpetta, Woodrow Shew, Oren Shriki, Thilo Womelsdorf. Workshop description ==================== Current information on the workshop can be found on the website http://www.h-w-k.de/index.php?id=2240 Soon we will update this web-page with the program . Cortical information processing relies heavily on the collective dynamics of neurons and networks distributed over many brain areas. A key concept for understanding this process is the idea that networks operate near a critical state, which offers several potential benefits for computation and information processing. However, there is still a large gap between research on criticality and understanding brain function: For example, * biological cortical networks are not homogeneous but highly structured, * they are not in a state of spontaneous activation but strongly driven by changing external stimuli, and * they process information with respect to a concrete behavioral goal. Moreover, critical states are just one side of the medal, since there are other concepts of how collective dynamics enables, shapes, and controls information processing; i.e. actively provide an operating point for cortical computation: To name just a few, there are * balance between excitation and inhibition, * temporal coordination and multiplexing, and * task-dependent computation and signal routing (selective attention). Understanding cortical function will only be possible by putting these conceptual ideas into a unifying framework and critically test them against experimental evidence. In this workshop we will bring together experts representing different approaches for understanding the collective dynamics of cortical networks and their implications for information processing. Hereby we will focus on work with a concrete link to cortical physiology, structure or dynamics observed in experiments. Our goals are to establish novel links between communities, concepts and methods and to identify key problems that have to be addressed by future theoretical and experimental work. Registration ============ The general costs of the workshop will be subsidized by the 'Hanse-Wissenschaftskolleg Institute for Advanced Study' (www.h-w-k.de) and by the BMBF (Bernstein Award Udo Ernst). However, in order to cover all costs, we ask for a registration fee in the amount of € 50,00 for PhD students and € 100,00 for postdocs/professors. Unfortunately, we cannot cover your costs for accommodation and travelling. Participation in the workshop will be limited to about 60 attendees (20 main speakers, 40 postdocs + PhD students). In case you are interested in participating, we would ask you to send your reply to Agnes Janssen ajanssen(a)neuro.uni-bremen.de. We can also arrange hotel reservations for you. Poster session ============== Besides the talks of the main speakers and plenty of time for discussions, there will be a poster session. You are invited to present a poster, in which case please send the title and abstract to Agnes Janssen. Again, we would greatly appreciate having you at our workshop. If you have any questions, please do not hesitate to contact us. Yours sincerely Udo Ernst and Nergis Tömen

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Post-Doc position at UCL Ear Institute: How the brain detects patterns in sound sequences
by Marcus Pearce Jan. 18, 2017

Jan. 18, 2017

Dear All (with apologies for cross-posting), *A postdoctoral research associate position*is available at the UCL Ear Institute’s ‘Auditory Cognitive Neuroscience Lab’ to work on a project entitled "How the brain detects patterns in sound sequences". The project will be supervised by Dr Maria Chait and conducted in collaboration with Dr. Marcus Pearce (Queen Mary University, London) and colleagues at the UCL Wellcome Trust centre for neuroimaging. The post is funded for 34 months in the first instance and involves a combination of behavioural, computational, eye tracking, and functional brain imaging (EEG, MEG, fMRI) experiments in humans. For more information about the post please see the lab website: *http://www.ucl.ac.uk/ear/research/chaitlab/vacancies* The Ear Institute is a leading interdisciplinary centre for hearing research in Europe, situated within one of the strongest neuroscience communities in the world at University College London *Key Requirements* The successful applicant will have a PhD in neuroscience or a neuroscience-related discipline and proven ability to conduct high-quality original research and prepare results for publication. Essential skills include excellent time-management and organizational ability; proficiency in computer programming and good interpersonal, oral and written communication skills. Previous experience with functional brain imaging, neural data analysis, psychophysical assessment, and/or auditory science or acoustics would be desirable. *Further Details* You should apply for this post (Ref #: 1618836) through UCL's online recruitment website, www.ucl.ac.uk/hr/jobs <http://www.ucl.ac.uk/hr/jobs>, where you can download a job description and person specifications. *Closing Date for applications is: *1 Feb 2017 *For an informal discussion please contact Dr. Maria Chait (m.chait(a)ucl.ac.uk).* Maria Chait PhD m.chait(a)ucl.ac.uk <mailto:m.chait@ucl.ac.uk> Reader in Auditory Cognitive Neuroscience Lab site: http://www.ucl.ac.uk/ear/research/chaitlab/ UCL Ear Institute 332 Gray's Inn Road London WC1X 8EE

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Faculty position in Computational Neuroscience - open rank
by Jorn Diedrichsen Jan. 18, 2017

Jan. 18, 2017

Western University (Ontario, Canada) is inviting applications from exceptional investigators at all career levels for a probationary (tenure-track) position at the rank of Assistant or Associate or a tenured faculty position at the rank of Associate or Professor in Computational Neuroscience. This appointment is in association with BrainsCAN (http://www.uwo.ca/brainscan) a $66M initiative funded by the Canada First Research Excellence Fund at Western University, and will be the first of two new positions in this area. For further particulars, please see: http://www.uwo.ca/bmi/media/CompNeuroScienceJan2017.pdf Jörn Diedrichsen Western Research Chair Brain Mind Institute Department of Computer Science Department of Statistics Email: jdiedric(a)uwo.ca<mailto:jdiedric@uwo.ca> Tel: 1-519-661-2111 x86994

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