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[IJCNN 2017] Upcoming deadlines for Tutorials and Workshop Proposals

by Teng Teck Hou

[Apologies for cross-postings] ############################################################ International Joint Conference on Neural Networks May 14-19, 2017, Anchorage, Alaska, USA http://www.ijcnn.org/ ##################### Important Dates ###################### * Tutorial and Workshop Proposals October 15, 2016 * Paper Submission November 15, 2016 * Paper Decision Notification January 20, 2017 * Camera-Ready Submission ebruary 20, 2017 #################### UPCOMING DEADLINES #################### CALL FOR WORKSHOPS http://www.ijcnn.org/call-for-workshops CALL FOR TUTORIALS http://www.ijcnn.org/call-for-tutorials [UPCOMING DEADLINES 23.59hr UTC-10 on Saturday, 15 OCTOBER 2016] ############################################################ The 2017 International Joint Conference on Neural Networks (IJCNN 2017) will be held at the William A. Egan Civic and Convention Center in Anchorage, Alaska, USA, May 14-19, 2017. The conference is organized jointly by the International Neural Network Society and the IEEE Computational Intelligence Society, and is the premiere international meeting for researchers and other professionals in neural networks and related areas. It will feature invited plenary talks by world-renowned speakers in the areas of neural network theory and applications, computational neuroscience, robotics, and distributed intelligence. In addition to regular technical sessions with oral and poster presentations, the conference program will include special sessions, competitions, tutorials and workshops on topics of current interest For the latest updates, follow us on Facebook (https://fb.me/ijcnn2017/) and Twitter (@ijcnn2017). #################### Paper Submission is now Open #################### http://www.ijcnn.org/call-for-papers * Regular paper can have up to 8 pages in double-column IEEE Conference format * All papers are to be prepared using IEEE-compliant Latex or Word templates on paper of U.S. letter size. * All submitted papers will be checked for plagiarism through the IEEE CrossCheck system. * Papers with significant overlap with the authors own papers or other papers will be rejected without review. ##########################Call for Workshops########################## Post-conference workshops offer a unique opportunity for in-depth discussions of specific topics in neural networks and computational intelligence. The workshops should be moderated by scientists or professionals who has significant expertise and /or whose recent work has had a significant impact within their field. IJCNN 2017 will emphasize emerging and growing areas of computational intelligence. Each workshop has a duration of 3 or 6 hours. The format of each workshop will be up to the moderator, and can include interactive presentations as well as panel discussions among participants. These interactions should highlight exciting new developments and current research trends to facilitate a discussion of ideas that will drive the field forward in the coming years. Workshop organizers can prepare various materials including handouts or electronic resources that can be made available for distribution before or after the meeting. Researchers interested in organizing workshops are invited to submit a formal proposal including the following information as a single file (pdf, doc, etc.) to the workshop chair: * Title * Organizers and their short bio * Brief description of the scope and impact of the workshop * Timeliness of the topic * Confirmed and/or potential speakers * Half day (3 hours) or full day (6 hours) * Link to organizer's web page and/or workshop web site (optional) For further details, please refer http://www.ijcnn.org/call-for-workshops. Any questions regarding this proposal can be asked to the Workshop Chair: Lazaros Iliadis, Democritus University of Thrace, Greece. E-mail: liliadis(a)fmenr.duth.gr ##########################Call for Tutorials########################## IJCNN 2017 will feature pre-conference tutorials addressing fundamental and advanced topics in computational intelligence. Tutorial proposals should be emailed to the Tutorial Chair (see below). A tutorial proposal should include the * Title * Presenter/organizer name(s) and affiliations * Expected enrollment * Abstract (less than 300 words) * Additional outline if needed * Presenter/organizer biography * Links to the presenter/organizer web page or the tutorial page (optional) * The proposal should not exceed two pages in 1.5 space, Times 12 point font. The tutorial format (preliminary) is 1 hour and 45 minutes with a 10-minute break. Researchers interested in organizing workshops are invited to submit a formal proposal. For further details, please refer to http://www.ijcnn.org/call-for-tutorials. Any questions regarding this proposal can be asked to the Tutorials Chair: Asim Roy, Arizona State University, USA. E-mail: ASIM.ROY(a)asu.edu ##################Topics and Areas of Interest################## This conference solicits papers addressing original works in topics and areas of interest including, but are not limited to: NEURAL NETWORK MODELS * Feedforward neural networks * Recurrent neural networks * Self-organizing maps * Radial basis function networks * Attractor neural networks and associative memory * Modular networks * Fuzzy neural networks * Spiking neural networks * Reservoir networks (echo-state networks, liquid-state machines, etc.) * Large-scale neural networks * Other topics in artificial neural networks MACHINE LEARNING * Supervised learning * Unsupervised learning and clustering, (including PCA, and ICA) * Reinforcement learning * Probabilistic and information-theoretic methods * Support vector machines and kernel methods * EM algorithms * Mixture models, ensemble learning, and other meta-learning or committee algorithms * Bayesian, belief, causal, and semantic networks * Statistical and pattern recognition algorithms * Visualization of data * Feature selection, extraction, and aggregation * Evolutionary learning * Hybrid learning methods * Computational power of neural networks * Deep learning * Other topics in machine learning NEURODYNAMICS * Dynamical models of spiking neurons * Synchronization and temporal correlation in neural networks * Dynamics of neural systems * Chaotic neural networks * Dynamics of analog networks * Neural oscillators and oscillator networks * Dynamics of attractor networks * Other topics in neurodynamics COMPUTATIONAL NEUROSCIENCE * Connectomics * Models of large-scale networks in the nervous system * Models of neurons and local circuits * Models of synaptic learning and synaptic dynamics * Models of neuromodulation * Brain imaging * Analysis of neurophysiological and neuroanatomical data * Cognitive neuroscience * Models of neural development * Models of neurochemical processes * Neuroinformatics * Other topics in computational neuroscience NEURAL MODELS OF PERCEPTION, COGNITION AND ACTION * Neurocognitive networks * Cognitive architectures * Models of conditioning, reward and behavior * Cognitive models of decision-making * Embodied cognition * Cognitive agents * Multi-agent models of group cognition * Developmental and evolutionary models of cognition * Visual system * Auditory system * Olfactory system * Other sensory systems * Attention * Learning and memory * Spatial cognition, representation and navigation * Semantic cognition and language * Neural models of symbolic processing * Reasoning and problem-solving * Working memory and cognitive control * Emotion and motivation * Motor control and action * Dynamical models of coordination and behavior * Consciousness and awareness * Models of sleep and diurnal rhythms * Mental disorders * Other topics in neural models of perception, cognition and action NEUROENGINEERING * Brain-machine interfaces * Neural prostheses * Neuromorphic hardware * Embedded neural systems * Other topics in neuroengineering BIO-INSPIRED AND BIOMORPHIC SYSTEMS * Brain-inspired cognitive architectures * Embodied robotics * Evolutionary robotics * Developmental robotics * Computational models of development * Collective intelligence * Swarms * Autonomous complex systems * Self-configuring systems * Self-healing systems * Self-aware systems * Emotional computation * Artificial life * Other topics in bio-inspired and biomorphic systems APPLICATIONS * Bioinformatics * Biomedical engineering * Data analysis and pattern recognition * Speech recognition and speech production * Robotics * Neurocontrol * Approximate dynamic programming, adaptive critics, and Markov decision processes * Neural network approaches to optimization * Signal processing, image processing, and multi-media * Temporal data analysis, prediction, and forecasting; time series analysis * Communications and computer networks * Data mining and knowledge discovery * Power system applications * Financial engineering applications * Applications in multi-agent systems and social computing * Manufacturing and industrial applications * Expert systems * Clinical applications * Big data applications * Smart grid applications * Other applications CROSS-DISCIPLINARY TOPICS * Hybrid intelligent systems * Swarm intelligence * Sensor networks * Quantum computation * Computational biology * Molecular and DNA computation * Computation in tissues and cells * Artificial immune systems * Other cross-disciplinary topics ################## Organizing Committee ###################### The full organizing committee can be found at: http://www.ijcnn.org/organizing-committee General Chair * Yoonsuck Choe, Texas A and M University, USA Program Chair * Christina Jayne, Robert Gordon University, UK Technical Co-Chairs * Irwin King, The Chinese University of Hong Kong, China * Barbara Hammer, University of Bielefeld, Germany ##################Sponsoring Organizations################## * INNS - International Neural Network Society * IEEE - Computational Intelligence Society * BSCS - Budapest Semester in Cognitive Science

Sept. 19, 2016

Postdoctoral fellowship in computational neuroscience at Harvard

by Jan Drugowitsch

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 psychophysics, computational modeling, and clinical studies. The project focuses on 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. Candidates must have a 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) Applications will be reviewed until the position is filled. Best, Jan Drugowitsch Assistant Professor in Neurobiology Harvard Medical School

Sept. 18, 2016

JOB: Neuroimaging Data Scientist. Multi-modal MRI study of voice perception.

by Sylvain Takerkart

The 4-year project LIVES (Learning with Interacting Views), funded by the French National Research Agency (ANR), aims at developing innovative multi-view and multi-modal machine learning algorithms. As part of the LIVES consortium, our team at the Institut de Neurosciences de la Timone (INT, http://www.int.univ-amu.fr) is in charge of acquiring a large *multi-sequence MRI* dataset that will be used to benchmark these methods. This will include *anatomical*, *diffusion-weighte*d and *functional* (both resting state and task-based) MRI data. Our goal is to characterize the inter-subject variability observed in the cortical activation patterns measured with task-based functional MRI in the auditory cortex, in a task that involves the processing of vocal information, using the other acquired modalities. *Missions*. The data scientist will set-up processing pipelines dedicated to analyze the different MR scan types (univariate and multi-voxel pattern analysis methods for task-fMRI; advanced characterization of the cortical anatomy using high-level representations such as sulci and sulcal pits; estimation of structural and functional connectomes). He/she will organize the raw and processed data in a standardized fashion in order to make it accessible to the other members of the consortium in a first stage, and to the scientific community at large in a second stage. *Profile*. This position is for a candidate who is comfortable (or proficient) with *computer programming* (*python* will be our language of choice), has knowledge in *signal and image processing* and has a personal interest for *machine learning*. It can be of interest to different types of profiles. Either you are a young graduate (BSc or MSc) in data science, electrical engineering or neuroscience and you want to be at the heart of a project where medical imaging and machine learning meet, with the possibility to continue as a PhD student. Or you already have a PhD in a relevant domain and you want to take this opportunity to fulfill the aforementioned missions while getting further involved in the research aspects of the project, in machine learning or in neuroimaging. *Working environment*. INT is one of the top French neuroscience research institutes with 150 staff members in 10 inter-disciplinary teams examining different aspects of the cerebral organization. It is located on the medical campus of Aix-Marseille University. The successful candidate will join INT’s Neuro-Computing Center, who operates a high-end computing facility and pursues research at the intersection of machine learning and neuroscience. He/she will interact with other teams working on functional imaging of voice perception, computational anatomy, machine learning and MRI data acquisition. Marseille, the second largest city in France, is a vibrant inter-cultural hub located on the Mediterranean shore, and only 2h away from the Alps mountains. The position is initially open for one year, with a possible renewal for a second year. Starting date is around December 2016. If you are interested, please send your resume and cover letter before Septembre 30, 2016, to Sylvain_DOT_Takerkart_AT_univ-amu_DOT_fr and Pascal_DOT_Belin_AT_univ-amu_DOT_fr. -- Sylvain Takerkart Institut des Neurosciences de la Timone (INT) UMR 7289 CNRS-AMU Marseille, France tél: +33 (0)4 91 324 007 http://www.int.univ-amu.fr/_TAKERKART-Sylvain_?lang=en

Sept. 15, 2016

Tenure-Track Position in Computational Neuroscience, University of Oregon

by Yashar Ahmadian

*Tenure track position in Computational Neuroscience* University of Oregon Departments of Mathematics and Biology (http://math.uoregon.edu/ http://biology.uoregon.edu/) Institute of Neuroscience (http://www.neuro.uoregon.edu/) The Departments of Biology and Mathematics and the Institute of Neuroscience at the University of Oregon announce a tenure track faculty position in computational neuroscience at the rank of assistant professor with ultimate department and institute affiliations flexible. Theorists seeking synergistic interactions with experimentalists in design, analysis and interpretation of research linking gene function, neuronal activity and behavior in model organisms and humans are especially encouraged to apply. This new position is part of an integrated effort to strengthen research at the nexus of mathematics and biology at the University of Oregon. It also advances a broader “Neurons to Minds” initiative that includes multiple new positions in systems and cognitive neuroscience to accelerate discovery in the neuronal basis of behavior and cognition. Minimum qualifications for candidates are a Ph.D. in an appropriate field (e.g. neuroscience, biology, mathematics, physics, electrical engineering, statistics, computer science, etc.), commitment to excellent teaching at the undergraduate and graduate levels, and an outstanding research record. Candidates should have the ability to work effectively within a diverse community. Applications will be received online at https://www.mathjobs.org/jobs/UO/IONMATHBIO. Candidates are asked to submit a cover letter, a curriculum vitae including a publication list, a statement of research accomplishments and future research plans, a description of teaching experience and philosophy, and three letters of recommendation (sent independently). Submission of 1-3 selected reprints is encouraged. To be assured of consideration, application materials should be uploaded by *November 15, 2016, but the position will remain open until filled*. Requests for information can be sent to Dr. Shawn Lockery, Chair, Computational Neuroscience Search Committee (shawn(a)uoregon.edu) *The University of Oregon is an equal opportunity, affirmative action institution committed to cultural diversity and compliance with the ADA. The University encourages all qualified individuals to apply, and does not discriminate **on the basis of any protected status, including veteran and disability status.* *---------------------------------------------* *Yashar Ahmadian* *Institute of Neuroscience* Departments of Biology and Mathematics *University of Oregon* *http://uoneuro.uoregon.edu/ahmadian/index.php <http://uoneuro.uoregon.edu/ahmadian/index.php>*

Sept. 15, 2016

Postdoc and Research Assistant openings in cognitive neuroscience at UCSF/Stanford

by Connolly, Colm

Please respond to info(a)brainlens.org<mailto:info@brainlens.org> Research Assistant Position at UCSF in California, USA on Multilingualism The Hoeft Lab (http://brainLENS.org PI: Fumiko Hoeft MD PhD) is looking for an exceptional research assistant interested in the developmental cognitive neuroscience of multilingualism. This NIH-funded research is in collaboration with Cammie McBride PhD of Chinese Univ of Hong Kong, Ken Pugh PhD of Haskins/Yale/UConn, Linda Siegel of UBC, Manolo Carreiras PhD of BCBL, Ioulia Kovelman PhD of U Michigan, and Yuuko Uchikoshi EdD of UC Davis. The position is suited for a self-motivated, organized and independent thinker, with good interpersonal and multitasking skills, as well as proficiency in the English language and computer software. Neuroimaging, computational, statistical, programming, and neuropsych testing skills are highly desired but not necessary. Native-like proficiency in Spanish or Cantonese is a plus. A major strength of our lab is that there are plenty of opportunities to conduct independent research, to be first author on publications and to give conference presentations as a novice RA (e.g. Myers et al. Psychol Sci ’14, Myers et al. SCAN ’16, Haft et al. Curr Opin Behav Sci ’16). The position begins in January but start date can be sooner and is negotiable. Please email info(a)brainlens.org with a cover letter and your CV. Please add “[RA job]” and your full name in the Subject of the email. Qualified candidates will be asked to have 2-3 letters of reference forwarded. Joint Postdoctocal Position at UCSF and Stanford University in California, USA The Hoeft Lab (http://brainLENS.org PI: Fumiko Hoeft MD PhD) at the UCSF Dept of Psychiatry and Weill Institute for Neurosciences in collaboration with the Stanford Mood and Anxiety Disorders Lab in the Dept of Psychology (http://goo.gl/dc96Cx PI: Ian Gotlib PhD) is looking for an exceptional postdoc in the field of affective neuroscience, with advanced neuroimaging, psychophysiology, computational, programming and organizational skills. Training in genetics is a plus. The primary project that the postdoc will be responsible for is the examination of intergenerational neuroimaging using a ‘natural’ cross-fostering design that allows dissociation of genetic, prenatal and postnatal environment on brain networks that are transmitted across generations. Related articles from our lab can be found here - Yamagata et al. J Neurosci 2016 (http://goo.gl/vMK8iy) Ho et al. Trends in Neurosci 2016 (http://goo.gl/SyXLcK) and Scientific American (http://goo.gl/YTiH6D) There are other funded opportunities to be involved in research that examines the impact of anxiety and stereotype on psychophysiology and cognitive processes. The position can begin immediately. Please email info(a)brainlens.org with your CV, and with brief paragraphs of research interests, career goals and why you feel you are a good fit for the lab. Please add “[Postdoc job]” and your full name in the Subject of the email. Qualified candidates will be asked to have 3 letters of reference forwarded. Regards, -- Colm G. Connolly PhD Dept of Psychiatry & Langley Porter Psychiatric Institute UCSF Weill Institute for Neurosciences University of California, San Francisco 401 Parnassus Avenue, San Francisco, CA 94143

Sept. 14, 2016

Conference Aspects of Neuroscience [Warsaw, Poland, 25-27th November]

by Daniel Borek

Dear Friends, On behalf of the Neurobiology Scientific Student Association at the Faculty of Biology of the University of Warsaw we would like to invite you to* the 6th annual International Conference “Aspects of Neuroscience” *to be held in Warsaw, Poland, from *November 25th to 27th, 2016*. As in previous years, the Conference is divided into 4 sessions presenting different approaches to Neuroscience:*Neurobiology, Cognitive Neuroscience, Clinical Neuroscience *and* Computational Neuroscience*. Each thematic session is opened by a lecture delivered by one of the guests who are specialists in a given domain. This year we will host such outstanding neuroscientists as *Prof. Eva Jablonka, Prof. Christian Lüscher, Prof. David Price, Prof. Kevin Warwick, Prof. Giovanna Mallucci *and* Dr. Daniel S. Margulies*. Participants are encouraged to give an oral presentation in one of the thematic sessions following the guest’s lecture or to present a poster during the poster session (either in the experimental or theoretical section). *Abstract submission deadline: 1st November 2016Passive registration deadline: 10th November 2016* The conference is intended for students, PhD students and research workers in neuroscience or related fields. The interdisciplinary character of the Conference is a base for integration of diverse scientific environments in order to create new quality in brain research. The language of the conference is English. *For more information about the Conference visit our new website:* http://neuroaspects.org <http://neuroaspects.us14.list-manage.com/track/click?u=c2e0466a746fafa55697…> Find us on Facebook: https://www.facebook.com/AspectsOfNeuroscience <http://neuroaspects.us14.list-manage.com/track/click?u=c2e0466a746fafa55697…> Yours sincerely, Organizing Committee of the International Conference Aspects of Neuroscience Neurobiology Scientific Student Association at the University of Warsaw

Sept. 13, 2016

Brains and Bits: Neuroscience Meets Machine Learning - NIPS Workshop: 9 & 10 December 2016

by Konrad Kording

Join us (submit papers to) for the *Brains and Bits: Neuroscience Meets Machine Learning* *NIPS Workshop: 9 & 10 December 2016 Barcelona, Spain* http://www.stat.ucla.edu/~akfletcher/brainsbits.html The goal of this workshop is to bring together researchers in deep learning, machine learning, statistics, and computational neuroscience, and facilitate discussion about a) shared approaches for analyzing biological and artificial neural systems, b) how insights and challenges from neuroscience can inspire progress in machine learning, and c) machine learning methods for interpreting the revolutionary large scale datasets produced by new experimental neuroscience techniques. We invite high-quality submissions of abstracts for posters and contributed talks though CMT. Instructions are below. OverviewExperimental methods for measuring neural activity and structure have undergone recent revolutionary advances, including in high-density recording arrays, population calcium imaging, and large-scale reconstructions of anatomical circuitry. These developments promise unprecedented insights into the collective dynamics of neural populations and thereby the underpinnings of brain-like computation. However, these next-generation methods for measuring the brain’s architecture and function produce high-dimensional, large scale, and complex datasets, raising challenges for analysis. What are the machine learning and analysis approaches that will be indispensable for analyzing these next-generation datasets? What are the computational bottlenecks and challenges that must be overcome? In parallel to experimental progress in neuroscience, the rise of deep learning methods has shown that hard computational problems can be solved by machine learning algorithms that are inspired by biological neural networks, and built by cascading many nonlinear units. In contrast to the brain, artificial neural systems are fully observable, so that experimental data-collection constraints are not relevant. Nevertheless, it has proven challenging to develop a theoretical understanding of how neural networks solve tasks, and what features are critical to their performance. Thus, while deep networks differ from biological neural networks in many ways, they provide an interesting testing ground for evaluating strategies for understanding neural processing systems. Are there synergies between analysis methods for biological and artificial neural systems? Has the resurgence of deep learning resulted in new hypotheses or strategies for trying to understand biological neural networks? Conversely, can neuroscience provide inspiration for the next generation of machine-learning algorithms? We welcome participants from a range of disciplines in statistics, applied physics, machine learning, and both theoretical and experimental neuroscience, with the goal of fostering interdisciplinary insights. We hope that active discussions among these groups can set in motion new collaborations and facilitate future breakthroughs on fundamental research problems. ------------------------------ Organizers - Eva Dyer <http://kordinglab.com/people/eva_dyer/> Northwestern University - Allie Fletcher <http://www.stat.ucla.edu/~akfletcher/> Statistics, UCLA & UCB Redwood Center for Neuroscience - Konrad Kording <http://koerding.com//> Rehabilitation Institute of Chicago, Northwestern University - Jascha Sohl-Dickstein <http://www.sohldickstein.com/> Google Research - Joshua Vogelstein <http://jovo.me/> Biomedical Engineering, Johns Hopkins University - Jakob Macke <http://www.mackelab.org/> caesar Bonn, an Institute of the Max Planck Society Current Speakers - Christos Papadimitriou <https://people.eecs.berkeley.edu/~christos/> EECS, UC Berkeley - Adrienne Fairhall <https://fairhalllab.com/> Psychology and Biophysics, University of Washington - Yoshua Bengio <http://www.iro.umontreal.ca/~bengioy/yoshua_en/index.html> Computer Science and Operations Research, Université de Montréal - Sophie Denève <http://iec-lnc.ens.fr/group-for-neural-theory/members/faculty-in-alphabetic…> Group for Neural Theory, LNC, DEC, ENS - Demis Hassabis <http://demishassabis.com/> Google DeepMind - Terry Sejnowski <http://www.salk.edu/scientist/terrence-sejnowski/> Howard Hughes Medical Institute and Salk Institute, UCSD - Mitya Chklovskii <https://www.simonsfoundation.org/simons-center-for-data-analysis/scda-neuro…> Simons Foundation - Anima Anandkumar <http://newport.eecs.uci.edu/anandkumar/> EECS, UC Irvine - David Cox <http://www.coxlab.org/> Molecular and Cellular Biology and Computer Science, Harvard University - Surya Ganguli <https://web.stanford.edu/dept/app-physics/cgi-bin/person/surya-gangulijanua…> Applied Physics, Stanford University - Maneesh Sahani <http://www.gatsby.ucl.ac.uk/~maneesh/> Gatsby Institute, University College, London - Emily Fox <https://www.stat.washington.edu/~ebfox/> Statistics and Computer Science, University of Washington - Jonathan Pillow <http://pillowlab.princeton.edu/> Center for Statistics and Machine Learning, Princeton University - Fred Hamprecht <https://hciweb.iwr.uni-heidelberg.de/people/fhamprec> Heidelberg Collaboratory for Image Processing (HCI), Heidelberg - Max Welling, University of Amsterdam Submission Information & Important Dates Submissions will be considered both for poster and oral presentation. See instructions on the workshop website at http://www.stat.ucla.edu/~ akfletcher/brainsbits.html Submission deadline: 29 September 2016 11:59 PM PDT (UTC -7 hours) Acceptance notification: 12 October 2016

Sept. 13, 2016

2 open faculty positions at U. Colorado Medical School

by Zylberberg, Joel L

Hello All, The Department of Physiology and Biophysics at the University of Colorado Medical School currently has two open tenure-track faculty positions. Specifically, we are searching for a new computational neuroscience / physiology faculty member, and for a new systems neuroscience / physiology faculty member. The positions at our medical school are quite nice for research-focused faculty: light teaching loads, extremely competitive start-up packages, etc. Details are available via this web link: http://www.ucdenver.edu/academics/colleges/medicalschool/departments/physio… If you have any questions, please don't hesitate to ask me. Also, please forward this advertisement to any colleagues of yours who might be interested. Thanks! __ Joel Zylberberg Assistant Professor Department of Physiology and Biophysics University of Colorado School of Medicine www.jzlab.org<http://www.jzlab.org> CIFAR Azrieli Global Scholar, Learning in Machines and Brains program ~the neuroscience is theoretical, but the fun is real

Sept. 12, 2016

Third International Conference on Mathematical Neuroscience (ICMNS 2017)

by Robert Rosenbaum

We are delighted to announce 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 (Tutorials: May 30; Main Conference: May 31 - June 2). http://www.colorado.edu/amath/international-conference-mathematical-neurosc… *Abstract submission will open in October/November for both contributed talks and posters. *Student presenters can apply for travel awards funded by NSF, Burroughs Wellcome, and SIAM. The conference provides a forum for researchers to discuss current mathematical innovations emerging in neuroscience. We hope to attract and train young researchers on current methods in mathematical neuroscience. The meeting will feature leaders in applied mathematics and neuroscience that are developing new mathematical techniques for understanding high-dimensional data sets, building models to capture activity patterns and emergent computation, and working closely with experimentalists to address targeted questions about brain function. 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) Ila Fiete (University of Texas) Stefano Fusi (Columbia University) Peter Thomas (Case Western Reserve University) Taro Toyoizumi (Riken Brain Science Institute) More TBA! We hope to see you in Boulder this coming May! All the best Zack Kilpatrick (University of Colorado) Julijana Gjorgjieva (Max Planck Institute for Brain Research) Robert Rosenbaum (University of Notre Dame) (conference chairs)

Sept. 12, 2016

PhD position in Computational/Systems Neuroscience @ the Institute of Neuroinformatics - ETH Zurich

by Benjamin Grewe

PhD position in Computational/Systems Neuroscience @ the Institute of Neuroinformatics - ETH Zurich – in vivo imaging of neural ensemble learning in awake behaving animals – We are looking for a PhD candidate with a strong motivation to understand neuronal information processing (NIP) as well as learning induced changes in NIP at the level of large neuronal ensembles. To investigate NIP we utilize cutting edge large scale in vivo population calcium imaging techniques that allow recording ensemble activity of hundreds of neurons in freely moving and head-fixed rodents during diverse learning behaviors. Ideal candidates have some expertise in a neuroscience related field. The PhD candidate will acquire a unique skill set to utilize miniaturized and very large-scale calcium imaging technologies and work closely with the PI to perform behavior experiments and post-hoc data analysis. Applicants should hold a diploma or Masters degree in a quantitative discipline (e.g. physics, informatics, mathematics, biomedical-engineering) or neurobiology/neuroscience (e.g. systems neuroscience, neurophysiology, cell physiology). Experience in data analysis using MATLAB/Python/R or similar programming languages and basic knowledge in computational or experimental neuroscience is beneficial. Proficiency in English and a team-oriented working attitude are crucial for the applicant’s success. Candidates should be willing to perform biological in vivo experiments in rodents with an intrinsic motivation to unravel neural algorithms of information processing and learning. Please submit your complete application as one PDF via email to bgrewe(a)ethz.ch <mailto:bgrewe@ethz.ch>. The application should include the following documents: • A cover letter that includes the main motivation for doing a PhD at the INI. • Contact details of 2 references (email and phone number). • CV outlining prior education, research and publications (if available) • Academic transcripts (bachelor, master/diploma). • 1-2 page personal research statement. The research statement should cover the applicant’s future career goals and research project interests. The INI offers advanced, interdisciplinary PhD training and participation in cutting edge neuroscience and neuroinformatics research projects. The institute is home to a lively and interactive educational atmosphere with highly competitive salaries. Successful candidates will participate in the ZNZ doctoral program (http://www.neuroscience.uzh.ch/en.html <http://www.neuroscience.uzh.ch/en.html>) where they receive additional theoretical and practical training. Compensation/salary will be paid according to the guidelines of the Swiss National Science Foundation. Successful candidates will receive their PhD from ETH Zurich. Applications will be accepted until the position is filled and will be reviewed upon receipt. The Swiss Federal Institute of Technology (ETH) in Zurich is consistently ranked the top university in continental Europe and is a leading player in research and education in Switzerland and worldwide. The INI is a joint institute of ETH and the University of Zurich with a primary research focus at the intersection of systems neuroscience and neuroinformatics. The mission of the institute is to discover key principles by which neural networks operate and process information. Comprising a diverse research portfolio (www.ini.uzh.ch <http://www.ini.uzh.ch/>) the INI is uniquely positioned to bridge the gap between traditional systems neuroscience, neurobiology, neuroinformatics and neuroengineering. --------------------------------------------------------------------- Benjamin F. Grewe Institute of Neuroinformatics @ ETH Zurich Winterthurerstrasse 190 CH-8057 Zurich, Switzerland Email: Bgrewe(a)ethz.ch

Sept. 12, 2016