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PhD position in Göttingen: Deep learning in the retina
by Ecker, Alexander Dec. 2, 2020

Dec. 2, 2020

PhD position in Göttingen, Germany: Deep neural network models to understand information processing in the retina A PhD position is available in the lab of Alexander Ecker at the University of Göttingen, Germany. Our group studies visual information processing in biological and artificial neural networks and works closely with experimental neuroscientists. At the interface of machine learning and computational neuroscience, we develop new methods and algorithms to make sense of large-scale neuroscience data and work on novel approaches to computer vision. We are looking for a highly motivated PhD student with a strong interest in developing deep learning tools for neuroscience and working closely with experimental neuroscientists. The ideal candidate has a background in computer science, mathematics or physics and experience with machine learning and deep neural networks. Prior experience in neuroscience is a plus, but not required. The project is part of the newly established Collaborative Research Center “Mathematics of Experiment” (https://www.uni-goettingen.de/en/628179.html<http://goettingen.de/en/628179.html>) and will be a collaboration with the lab of Tim Gollisch (University Medical Center Göttingen). The goal of the project is to record spiking activity from the retina under various visual stimuli (including natural stimuli) and study the signal processing in the inner retina with modern data science methods, including convolutional neural networks and deep learning. Our research group if part of the strong and lively neuroscience research community of Göttingen, including the University, the University Medical Center, several Max Planck Institutes, the German Primate Center, and the European Neuroscience Institute. We are also part of the Campus Institute Data Science (http://uni-goettingen.de/cidas) and the Bernstein Center for Computational Neuroscience Göttingen (https://www.uni-goettingen.de/en/615355.html) For more information about the research group, please visit our website: https://eckerlab.org. The position is for three years, with a possibility for extension. Please send your application to Alexander Ecker (ecker(a)cs.uni-goettingen.de<mailto:ecker@cs.uni-goettingen.de>) including a CV, a statement of what interests you in science and in the work of our research group, and contact details for two references. The University of Göttingen is an equal opportunity employer, and women are especially encouraged to apply. Applicants with disabilities and equal qualifications will be given preferential treatment. -- Alexander Ecker Professor of Data Science Department of Computer Science • Campus Institute Data Science University of Göttingen • Goldschmidtstr. 1 • room 2.137 • 37077 Göttingen https://eckerlab.org • @alxecker • +49 551 39-21272

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Computational Neuralengineering Training Program at Georgia Tech/Emory
by Rozell, Christopher J Dec. 1, 2020

Dec. 1, 2020

The Georgia Tech/Emory Computational Neuralengineering Training Program (CNTP) is a collaborative partnership with the mission of training the next generation of researchers at the intersection of computational neuroscience, data science and clinical neurophysiology. The CNTP is a training program supported by the National Institute of Biomedical Imaging and Bioengineering (NIBIB) to address the opportunities provided by the explosion of tools for measurement and manipulation of nervous system function and the challenges posed by neurologic disorders. Trainees in CNTP program consists of PhD students with clear interest in quantitative training and either basic or clinical study of the brain, and who are pursuing studies in any of these degree programs: Biomedical Engineering (GT and Emory), Bioengineering (GT), Electrical and Computer Engineering (GT) or Machine Learning (GT) PhD programs. In addition to the benefits of being part of the broad computational neuroscience community in Atlanta, CNTP trainees have access to a new restricted course on Clinical Experience for Engineers, regular meetings with the cohort for rich discussions in technical and professional development topics, and an annual retreat with faculty and students for deeper dives into research discussions. Fellows in the CNTP receive two years of funding which supports a rotation program between labs in the first year. Fellow applications are solicited in the spring from applicants to the degree programs listed above. To be considered for the CNTP Fellowship, all you need to do is apply to a participating graduate program and have aligned interests expressed in your research statement. Scholars in the CNTP are full members of the community with access to all of the same programming (but without the fellowship funding). Scholar applications will be solicited in the summer from students joining labs in the upcoming fall. While there are low barriers to performing interdisciplinary research across departmental boundaries, admissions are handled separately by each degree program. Students interested in participating in the CNTP program should apply to the program that best fits their goals and interests. Application deadlines are listed below, along with the CNTP training faculty affiliated with each degree program. Please contact crozell(a)gatech.edu with questions. ***DEGREE PROGRAMS*** Biomedical Engineering (GT and Emory) DEADLINE: December 1 Application information: https://www.bme.gatech.edu/bme/grad-prospective-student-apply Bioengineering (GT) DEADLINE: Same as the home school selected during application Application information: https://bioengineering.gatech.edu/applying-bioengineering-program Electrical and Computer Engineering (GT) DEADLINE: December 16 Application information: https://www.ece.gatech.edu/graduate-admissions Machine Learning (GT) DEADLINE: Same as the home school selected during application Application information: http://ml.gatech.edu/phd/admissions ***CNTP Training faculty*** --Georgia Tech-- Garrett Stanley Chris Rozell Rob Butera Hannah Choi Tim Cope Constantin Dovrolis Eva Dyer Irfan Essa Ross Ethier Bilal Haider Hang Lu Susan Margulies Cassie Mitchell Machelle Pardue Peng Qiu Annabelle Singer --Emory University-- Lena Ting Michael Borich Gordon Berman Nick Boulis Gary Clifford Bob Gross Shawn Hochman, Dieter Jaeger Shella Keilholz Robert Liu Babak Mahmoodi Svetlana Miocinovich Ilya Nemenman Chethan Pandarinath Astrid Prinz Sam Sober Thomas Wichmann

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PhD position in Göttingen: Combining retina recordings and artificial neural networks
by Gollisch, Tim Dec. 1, 2020

Dec. 1, 2020

PhD position in Göttingen: Combining retina recordings and artificial neural networks A PhD position is available in the lab of Tim Gollisch at the University Medical Center Göttingen, Germany. The group studies information processing and neural coding in the neural network of the vertebrate retina, using a combination of electrophysiological and computational approaches. Experimental methods include extracellular multielectrode-array recordings from neurons in the isolated retina (mouse and salamander), using both wild-type retinas and optogenetic retina models of vision restoration therapy. The focus of the group is to combine these experiments with novel tools for data analysis and mathematical modeling. We are looking for a highly motivated PhD student with a strong interest in combining experimental electrophysiology, computational neuroscience, and analysis of artificial neural networks. Experience in computer programming is a plus. The project is part of the newly established Collaborative Research Center "Mathematics of Experiment" (https://www.uni-goettingen.de/en/628179.html) and will be a collaboration with the lab of Prof. Alexander Ecker (University of Göttingen, Institute of Computer Science). The goal of the project is to record spiking activity from the retina under various visual stimuli (including natural stimuli) and analyze the retinal signal processing with modern data science methods, including convolutional neural networks and deep learning. Our research group if part of the strong and lively neuroscience research community of Göttingen, including the University, several Max Planck Institutes, the German Primate Center, and the European Neuroscience Institute. We are also part of the Bernstein Center for Computational Neuroscience Göttingen (https://www.uni-goettingen.de/en/615355.html) and of the Collaborative Research Center "Cellular Mechanisms of Sensory Processing" (http://sfb889.uni-goettingen.de/) For more information about the research group, please visit the group's website: https://www.retina.uni-goettingen.de/. The position is for 3 years, with a possibility for extension. Please send your application to Tim Gollisch (tim.gollisch(a)med.uni-goettingen.de<mailto:tim.gollisch@med.uni-goettingen.de>), including a CV, a statement of what interests you in science and in the work of our research group, and contact details for two references. The University Medical Center Göttingen is an equal opportunities employer, and women are especially encouraged to apply. Applicants with disabilities and equal qualifications will be given preferential treatment. -- Prof. Dr. Tim Gollisch University Medical Center Goettingen, Dept. of Ophthalmology Waldweg 33, 37073 Goettingen Tel. +49 (0)551 39-13542 tim.gollisch(a)med.uni-goettingen.de<mailto:tim.gollisch@med.uni-goettingen.de> www.retina.uni-goettingen.de<http://www.retina.uni-goettingen.de>

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GEM 2021 - Call for papers - deadline extended
by Vinita Samarasinghe Nov. 30, 2020

Nov. 30, 2020

The deadline to submit abstracts for the GEM 2021 workshop has been extended until 30.11.2020. Please visit https://easychair.org/cfp/gem2021 to submit your abstracts for both the main workshop and the PhD symposium. ** *GEM 2021 - Generative Episodic Memory: Interdisciplinary perspectives from psychology, neuroscience and philosophy* https://for2812.rub.de/gem2021 16-18 February 2021 The workshop will take place in virtual space and is free of charge. Abstracts for both the workshop and the PhD symposium, which will precede the workshop, are now being accepted via EasyChair https://easychair.org/cfp/gem2021 Keynote Speakers: Karl-Heinz Bäuml - University Regensburg, Germany Dorthe Berntsen - Aarhus University, Denmark Amy Criss - Syracuse University, USA Dorothea Debus - University of Konstanz, Germany David Huber - University of Massachusetts, USA Sarah Robins - University of Kansas, USA Call for papers The DFG-funded research consortium “FOR 2812 – Constructing scenarios of the past” https://for2812.rub.de is proud to announce a call for papers for its first workshop on generative episodic memory. We invite submissions for talks and posters https://easychair.org/cfp/gem2021. Episodic memories are widely regarded as memories of personally experienced events. Early concepts about episodic memory were based on the storage model, according to which experiential content is preserved in memory and later retrieved. However, overwhelming empirical evidence suggests that the content of episodic memory is – at least to a certain degree – constructed in the act of remembering. Even though very few contemporary researchers would oppose this view of episodic memory as a generative process, it has not become the standard paradigm of empirical memory research. This is particularly true for studies of the neural correlates of episodic memory. Further hindering progress are large conceptual differences regarding episodic memory across different fields, such as neuroscience, philosophy, and psychology. This interdisciplinary workshop therefore aims to bring together researchers from all relevant fields to advance the state of the art in the research on generative episodic memory. FOR 2812 “Constructing scenarios of the past: A new framework in episodic memory” consists of 9 researchers. Seven from the Ruhr University Bochum and two from the University of Münster. The consortium adopts an interdisciplinary approach and investigates generative episodic memory from a conceptual, modeling, and experimental perspective using a common conceptual framework: scenario construction. Paper submission deadlines [GMT +1 (CET)]: Abstract submission - 30.11.2020 Notification of acceptance - 31.12.2020 Submission guidelines: Abstracts must be submitted in English and be no longer than 1 page. Submitted work must be original and unpublished. Abstracts must be submitted electronically through the GEM 2021 paper submission site on EasyChair https://easychair.org/cfp/gem2021. Authors will receive confirmation of receipt of their abstracts including an ID number after submission. You can edit your submission at any time before the deadline. We will consider only the final version. Program committee: Nikolai Axmacher - Faculty of Psychology - Ruhr University Bochum Sen Cheng - Institute for Neural Computation - Ruhr University Bochum Gerald Echterhoff - Faculty of Psychology - University of Münster Albert Newen - Faculty of Philosophy - Ruhr University Bochum Ricarda Schubotz - Faculty of Psychology - University of Münster Markus Werning - Faculty of Philosophy - Ruhr University Bochum Laurenz Wiskott - Institute for Neural Computation - Ruhr University Bochum Oliver Wolf - Faculty of Psychology - Ruhr University Bochum All questions regarding the workshop should be emailed to for2812(a)rub.de <mailto:for2812@rub.de> Coordinator - Vinita Samarasinghe Secretary - Christiane Dahl Vinita Samarasinghe M.Sc., M.A. Science Manager Arbeitsgruppe Computational Neuroscience Institut für Neuroinformatik Ruhr-Universität Bochum, NB 3/26 Postfachnummer 110 Universitätstr. 150 D-44801 Bochum Tel: +49 (0)234 32 27996 Email: samarasinghe(a)ini.rub.de

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[jobs] Postdoc and internship position at AI Lab, Novaquark, Montreal (possibility for remote work)
by Pierre-Yves Oudeyer Nov. 26, 2020

Nov. 26, 2020

Novaquark AI Lab, Postdoc or PhD-level internship open position Title: Intention modeling and joint attention for deep reinforcement learning agents interacting with non-expert caretakers Supervision: Jean-Christophe Baillie Team: Novaquark AI Lab, Montréal Duration: 12-36 months for postdocs, 6 months for PhD-level internships, starting early 2021. Location: in Montréal Lab, or in remote. Keywords: Deep reinforcement learning; language grounding; artificial curiosity; developmental AI; joint attention Details: https://drive.google.com/file/d/1kJl851ciJj9lOU0gZ66zjkiMRLgvSgNZ/view <https://drive.google.com/file/d/1kJl851ciJj9lOU0gZ66zjkiMRLgvSgNZ/view> How to apply: contact ailab(a)novaquark.com with a CV and letter of motivation.

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NEUROTECH Webinar: What are the hardware opportunities for neuromorphic engineering?
by Elisa Donati Nov. 25, 2020

Nov. 25, 2020

We are back with the second NEUROTECH educational webinar on Neuromorphic Computing Technologies! We will have one hour of educational material followed by a panel discussion on the open challenges in the field. Please see below the details and please spread the word! ----- At the second webinar, Prof. Johannes Schemmel, Prof. Jennifer Olson Hasler, Dr. Elisa Vianello and Dr. Bert Jan Offrein will be answering the question “What are the hardware opportunities for neuromorphic engineering?”. Join us on the 1st of December at 16:00 CET. Sign up here for free: https://neurotech.iniforum.ch/educational/ <https://neurotech.iniforum.ch/educational/> ------------------------------------------------------------------------ About NEUROTECH: Our mission is to catalyse research and collaboration in NCT. Today's neuromorphic community in Europe is leading the state of the art in this domain. The community counts an increasing number of labs that work on theory, modelling, and implementation of neuromorphic computing systems. The NEUROTECH Project will create a Cartography of NCT in Europe, explore Roadmaps for its development, collect educational and information resources on NCT, and inform about upcoming and previous events. https://neurotech.iniforum.ch <https://neurotech.iniforum.ch/> NEUROTECH Educational Webinar: As part of the NEUROTECH project, the Educational Team is organizing a webinar series on neuromorphic computing technologies. The objective is to collect educational material about the field but also hold discussions with the experts about how the field started, how it evolved, where it’s going and how it’s going to shape the future industrial landscape. Follow us on LinkedIn: NEUROTECHAI and Twitter: JoinNeurotech ————————————————————————— Elisa Donati, PhD Research Fellow Institute of Neuroinformatics University of Zurich and ETH Zurich Winterthurerstrasse 190, 8057 Zurich E-mail: elisa(a)ini.uzh.ch, eldonati(a)ethz.ch Phone: +41 0446353061 Website: www.ini.uzh.ch/people/elisa

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Open positions in Computational Neuroscience and ML (Denmark / UK)
by Diego Vidaurre Nov. 25, 2020

Nov. 25, 2020

Dear all, Apologies for cross-posting. Funded by an ERC grant, I have two open postdoc positions in my lab in Aarhus University in collaboration with Oxford University, to develop new methods on machine learning and Bayesian time series modelling, with application to specific problems in computational neuroscience. The deadline is on the 30th of May. The positions are initially for 1y, but the idea is to offer longer funding, for up to 5y. https://health.au.dk/en/about-health/vacant-positions/job/postdoc-in-integr… Many thanks d

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CFP: FLAIRS 2021 Special Track Neural Nets and Datamining, May 16-19, N Miami Beach, FL
by David B Nov. 24, 2020

Nov. 24, 2020

Covid Update: FLAIRS will virtualize some or all of the conference,as necessary. FLAIRS is an interdisciplinary conference featuring a double-blind review and free tutorials, sponsored by the Association for the Advancement of Artificial Intelligence (AAAI) www.FLAIRS-34.info May 16-19, 2021 DoubleTree Ocean Point Resort & Spa, North Miami Beach, Florida, USA Paper submission deadline: February 16, 2021 This special track will be devoted to neural networks and data mining with the aim of presenting new and important contributions in these areas. Who might be interested? Papers and contributions are encouraged for any work related to Neural Networks and Data Mining. What kind of studies will be of interest? This special track will be devoted to neural networks and data mining with the aim of presenting new and important contributions in these areas. Papers and contributions are encouraged for any work related to neural networks, data mining, or the intersection thereof. Topics of interest may include (but are in no way limited to): 1. Applications such as Pattern Recognition, Control and Process Monitoring, Biomedical Applications, Robotics, Text Mining, Diagnostic Problems, Telecommunications, Power Systems, Signal Processing; Intelligence analysis, medical and health applications, text, video, and multi-media mining, E-commerce and web data, financial data analysis, cyber security, remote sensing, earth sciences, bioinformatics, and astronomy. 2. Algorithms such as new developments in Back Propagation, RBF, SVM, Deep Learning, Ensemble Methods, Kernel Approaches; hybrid approaches such as Neural Networks/Genetic Algorithms, Neural Network/Expert Systems, Causal Nets trained with Backpropagation, and Neural Network/Fuzzy LogicApplications such as Intelligence analysis, medical and health applications, text, video, and multi-media mining, E-commerce and web data, financial data analysis, cyber security, remote sensing, earth sciences, bioinformatics, and astronomy. 3. Modeling algorithms such as hidden Markov models, decision trees, neural networks, statistical methods, or probabilistic methods; case studies in areas of application, or over different algorithms and approaches. 4. Feature extraction and selection. 5. Post-processing techniques such as visualization, summarization, or trending. 6. Preprocessing and data reduction. 7. Knowledge engineering or warehousing. Papers dealing with Cloud-based unstructured data or Cloud-based tool suites, such as Mahout or Apache Spark, are also encouraged. Track Co-Chairs: David Bisant, Central Security Svcs, bisant(a)umbc.edu Steven Gutstein, Army Research Laboratory, s.m.gutstein(a)gmail.com William Eberle, Tennessee Tech University, weberle(a)tntech.edu Submission Instructions Submitted papers must be original, and not submitted concurrently to a journal or another conference. Full oral presentation papers may be up to 6 pages, short poster presentation papers up to 4 pages, and abstract only poster presentations up to 250 words. Submissions for special tracks, workshops, tutorials, and discussion panels are also welcome. Papers must be in AAAI format, and submitted as PDF through the EasyChair conference system, which can be accessed through the main conference web site http://www.flairs-34.info/. The proceedings of FLAIRS-34 will be published by Florida Online Journals (https://journals.flvc.org/) In order for a paper to be published in the proceedings, the paper must be accompanied by at least one AUTHOR REGISTRATION. It is also expected that for a full (i.e., maximum 6-page) paper, at least one of the authors will attend the conference to present their work. In order for a poster to be presented at the conference, it must also be accompanied by an AUTHOR REGISTRATION. Organization Conference Chair: Keith Brawner, Army Research Lab, USA Roman Barták, Charles University, Czech Republic Program Co-Chairs: Eric Bell, USA Fazel Keshtkar, St John’s University, USA

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Closed-Loop Deep Learning with Robotics, NECO Vol 32, No 11
by Sama Daryanavard (PGR) Nov. 23, 2020

Nov. 23, 2020

Dear Colleagues, In our paper we present Closed-Loop Deep Learning which combines the power of deep learning and classical control to create an efficient analogue multi-layered fast learning paradigm, for robotic navigation. At the heart of this algorithm is an error signal that arises from a reflex which is delicately used to both drive the closed loop system and train the deep learner simultaneously. Through mathematical derivation in z-space we show how to implement back-propagation in a closed-loop system. Preprint: https://arxiv.org/abs/2001.02970 Neural Computation (final version): https://www.mitpressjournals.org/doi/abs/10.1162/neco_a_01317?journalCode=n… Please do not hesitate to get in touch for a copy of the paper and to discuss your thoughts. Warmest Regards, Sama Daryanavard Dr Bernd Porr Biomedical Engineering Division, School of Engineering, University of Glasgow, Glasgow G12 8QQ, U.K.

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PhD programs in computational and theoretical neuroscience at the University of Washington
by Adrienne L Fairhall Nov. 23, 2020

Nov. 23, 2020

Looking for PhD opportunities? Join the vibrant, collaborative theoretical/computational neuroscience community at University of Washington in Seattle! Research areas span the full spectrum of scales, mechanisms, and functions of the brain — from the cellular biophysics of computation to brainwide models of neural processing and cognition to next-generation brain/computer interfaces. The Computational Neuroscience Center <https://cneuro-web01.s.uw.edu>, directed by Adrienne Fairhall and Eric Shea-Brown, is a hub for research in mathematical and computational neuroscience, connecting researchers at the University of Washington across campus and to the extended neuroscience community in the Pacific Northwest including the Allen Institute <https://alleninstitute.org/what-we-do/brain-science/>. UW is home to the Center for Neurotechnology <http://www.csne-erc.org/>, a leader in BCI technologies and neuroethics, and a member of the Weill Neurohub <https://www.weillneurohub.org/>, which collaboratively links UW with researchers with the neuroscience communities at UCSF and UC Berkeley. Specialized training is available in data science through the eScience Institute <https://escience.washington.edu>. Please visit our webpage <https://cneuro-web01.s.uw.edu> to learn more about faculty research interests and our wide range of community activities. The neuroscience community at UW is interdisciplinary, and students have the freedom to work across departments. Programs of interest to students wishing to study computational neuroscience include (w/ computational faculty in bold): NEUROSCIENCE <https://grad.uw.edu/admission/find-a-program/program-detail/#!?progid=76>(Deadline Nov. 30): faculty include Nick Steinmetz, Wyeth Bair, Anitha Pasupathy, Beth Buffalo, Bing Brunton, Ione Fine, David Gire, Jeff Ojemann, Adrienne Fairhall, Eric Shea-Brown, Jeff Riffell, Steve Perlmutter, Fred Rieke, John Tuthill COMPUTER SCIENCE <https://grad.uw.edu/admission/find-a-program/program-detail/#!?progid=29> (Deadline Dec. 15): faculty include Raj Rao APPLIED MATH <https://grad.uw.edu/admission/find-a-program/program-detail/#!?progid=3> (Deadline Dec. 15): faculty include Eric Shea-Brown, Nathan Kutz, Eli Shlizerman, Bing Brunton, and Adrienne Fairhall as well as Allen Institute affiliate faculty Michael Buice and Stefan Mihalas BIOLOGY <https://grad.uw.edu/admission/find-a-program/program-detail/#!?progid=641> (Deadline December 1): faculty include Bing Brunton, David Perkel, Jeff Riffell, Tom Daniel ELECTRICAL ENGINEERING <https://grad.uw.edu/admission/find-a-program/program-detail/#!?progid=213> (Deadline Dec. 15): faculty include Chet Moritz, Amy Orsborn, Azadeh Yazdan-Shahmorad, Howard Chizeck BIOENGINEERING <https://grad.uw.edu/admission/find-a-program/program-detail/#!?progid=14> (Deadline Dec. 1): Faculty include Amy Orsborn, Azadeh Yazdan-Shahmorad, Jay Rubinstein PSYCHOLOGY <https://grad.uw.edu/admission/find-a-program/program-detail/#!?progid=97> (Deadline Dec. 1): Faculty include Sheri Mizumori, Ariel Rokem, David Gire, Ione Fine, Geoff Boynton, Eliot Brenowitz, Andrea Stocco BIOSTATISTICS <https://grad.uw.edu/admission/find-a-program/program-detail/#!?progid=177> (Deadline December 1): Faculty include Daniela Witten and Ali Shojaie PHYSICS <https://grad.uw.edu/admission/find-a-program/program-detail/#!?progid=95> (Deadline Jan 5. ): faculty include Adrienne Fairhall, Fred Rieke

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