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Two PhD Positions in Machine Learning/Neuroimaging at Charité Berlin
by Stefan Haufe Sept. 11, 2019

Sept. 11, 2019

Dear all, The Brain and Data Science Lab of Stefan Haufe at Charité - Universitätsmedizin Berlin is looking to recruit two highly motivated PhD students. Appointments can be made for four years starting immediately. 1. Theory and practice of interpreting machine learning models Machine learning systems have recently set new standards for solving a wide range of problems by leveraging vast amounts of training data. But they have remained “black boxes” whose internal workings are too complex to be comprehensible by a human. Especially in the health domain, it is desirable to explain and visualize the decisions of ML models. Recently, it has been shown that many existing explanation methods can be misleading even when using simple linear ML models [Haufe et al., 2014; Kindermans et al., 2018]. In this PhD project, a bottom-up approach will be performed, in which correct interpretation will be defined axiomatically. The resulting definition will be used to benchmark novel and existing explanation methods using synthetic ground-truth data. The resulting methodology will also be applied to clinical use cases. 2. Estimating and characterizing EEG/MEG functional connectomes in aging and dementia The study of functional brain interactions promises to greatly enhance our understanding of mental diseases. EEG and MEG make it possible to brain dynamics at high temporal scales but suffer from low spatial resolution, which often leads to false detections of brain connectivity. While the problem has been overcome for linear connectivity metrics [Nolte et al., 2004; Haufe et al., 2013] it still persists for non-linear interactions such as phase-amplitude and amplitude-amplitude coupling, which have been postulated as possible mechanisms of brain communication. This PhD project will establish a best practice to reconstruct non-linear connectivity from EEG/MEG data. The developed pipeline will be applied to study brain connectivity in aging and neurological conditions (dementia) using big EEG/MEG datasets. Interpretable machine learning will further be used to relate functional connectomes to behavior and relevant clinical variables. The Brain and Data Science Group at Charité develops machine learning and signal processing methods for the analysis of non-invasive brain signals in health and disease. We are located at the Berlin Center for Advanced Neuroimaging (BCAN) on the beautiful historic Charité Campus Mitte in the center of Berlin, and are embedded in a stimulating inter-disciplinary research environment. The group is funded by an ERC starting grant of the European Union. Requirements: Candidates are expected to hold a very good MSc or equivalent degree preferably in a technical field (machine learning, computer science, statistics, mathematics, computational (neuro) science, data science, physics, electrical/biomedical engineering, etc.). All positions require a solid math/statistics background, proficiency in written English, and good coding skills (e.g., Matlab, Python, C++, Java). Prior experience with functional neuroimaging data is a plus. Applications should include a letter of motivation, a CV, transcripts and degree certificates, as well as (if available) references, an English-language writing sample, and a coding sample (e.g. link to a github project). Applications should be sent to stefan.haufe(a)charite.de until Oct 15th 2019. All attached documents should be contained in a single pdf. See braindata.charite.de for further information on the positions and our group. With best wishes, Stefan Haufe -- Stefan Haufe ERC Research Group Leader Charité - Universitätsmedizin Berlin Berlin Center for Advanced Neuroimaging (BCAN) Charitéplatz 1 Sauerbruchweg 4 10117 Berlin Tel: +49 30 450 639 639 Fax: +49 30 450 539 951 Web: braindata.charite.de

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post-doc position at the University of Bern
by Jean-Pascal Pfister Sept. 11, 2019

Sept. 11, 2019

The Department of Physiology, University of Bern, is looking to hire a theoretical and/or computational neuroscientist at the postdoctoral level. A PhD in computational/theoretical neuroscience or a closely related field, along with a desire to work tightly with experimentalists would be strongly recommended. The aim of the project is to (a) propose an experimentally testable theory of predictive coding, (b) derive specific testable predictions at the single cell resolution, (c) test them by analyzing existing experimental data obtained in the Department and (d) propose new experiments than can be conducted in the Department. The specificity of the project is the closed-loop interactions between theory and experiments. The candidate will have access to experimental data acquired within the research groups of Thomas Nevian, Shankar Sachidhanandam and Stéphane Ciocchi. These groups focus on cortical function, ranging from sensory perception and predictive processing to emotional state transitions and memory formation in head-fixed and freely moving mice. Supervision will be provided by Prof. Jean-Pascal Pfister of the Theoretical Neuroscience Group, along with close collaboration with the experimental groups. The candidate can further benefit from interactions with members of the computational neuroscience group of Walter Senn specializing in deep learning. Interested candidates can send their application and inquiries via email to pfister(a)pyl.unibe.ch <mailto:pfister@pyl.unibe.ch>. The application should include the following as one pdf document: letter of motivation, CV, contact details of 2 references, 1 page research statement covering future research goals and project interests. Deadline for application is the 31st of October 2019 or until the position is filled. --------------------------------- Prof. Jean-Pascal Pfister Department of Physiology University of Bern Bühlplatz 5 3012 Bern, Switzerland and Theoretical Neuroscience Group Institute of Neuroinformatics University of Zurich and ETH Zurich Winterthurerstrasse 190 8057 Zurich, Switzerland www.ini.uzh.ch/~jpfister <http://www.ini.uzh.ch/~jpfister> Tel: ++ 41 31 631 87 78

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Registration is open for NeuroEng 2019: The 12th Australasian Workshop on Computational Neuroscience & Neural Engineering (November 29-30)
by Steven Wiederman Sept. 10, 2019

Sept. 10, 2019

Bringing together computational neuroscientists and researchers at the interface between neuroscience and engineering (neuroeng.org.au<http://neuroeng.org.au/phpList/lt.php?id=fE0DA1oeU1VLVAgO>) NeuroEng 2019 will be hosted at The University of Adelaide, South Australia. Please feel free to distribute the NeuroEng poster available here.<http://neuroeng.org.au/phpList/lt.php?id=fE0DA1seU1VLVAgO> Keynote speakers: Professor Barbara Webb (University of Edinburgh) & Professor Yves De Koninck (Univeriste Laval) • Theoretical, Mathematical & Computational Neuroscience • Neuroprosthetics & Brain Machine Interfaces • Neural Modelling & Engineering • Neuromorphic Engineering • EEG Analysis • Neural Information Processing • Neuroinformatics • Cognitive Modelling • Neuroimaging & Connectomics • Brain Dynamics & Neurophysics The Abstract Template is available here<http://neuroeng.org.au/wordpress/wp-content/uploads/2019/07/NeuroEng2019_Ab…> Please email 1 page abstracts to admin(a)neuroeng.org.au<mailto:admin@neuroeng.org.au> (deadline, 20th September). In your email submission, please provide a preference for oral or poster presentation. Registration is now open at this link.<http://www.conferenceonline.com/conference_invitation/22847/?key=4FB9B222-4…> Early bird pricing (ends 20th September). Students $220 (ex GST), General $360 (ex GST). Registration includes Welcome Reception (drinks & canapes) and Workshop Dinner. The Welcome Reception will be held Thursday evening (November 28th). The Workshop dinner will be held at Jolley’s Boathouse (November 29th). This meeting will be held as a satellite of the Australasian Neuroscience Society (ANS) conference (Dec 2-5), so please consider scheduling your time for both events. If you have any questions, please do not hesitate to contact me Dr Steven Wiederman +61 403 079 575, steven.wiederman(a)adelaide.edu.au<mailto:steven.wiederman@adelaide.edu.au> regards, Steve --- Dr Steven Wiederman<mailto:steven.wiederman@adelaide.edu.au> +61 403 079 575 ARC Future Fellow, Visual Physiology & Neurobotics Laboratory Adelaide Medical School, The University of Adelaide

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Reminder: Special Entropy Issue "Information Theory in Computational Neuroscience"
by Dimitrije Markovic Sept. 10, 2019

Sept. 10, 2019

Dear Colleagues, You are cordially invited to submit a manuscript to Special Entropy Issue "Information Theory in Computational Neuroscience" https://www.mdpi.com/journal/entropy/special_issues/Computational_Neuroscie… Deadline for manuscript submissions: 31 January 2020 With best regards, Claudius Gros and Dimitrije Markovic Abstract ====== Brains empower living organisms with extraordinary information processing capabilities. Complex spatio-temporal dependencies present in their environments may be learned, long- and short-term memories of experiences and plans regarding the future. Importantly, information processing in the brain happens over multiple spatio-temporal scales, from single synapses and synaptic terminals to dendritic trees and neuronal bodies, all the way up to neuronal networks and large brain areas. Hence, it is not surprising that information theory has led to many exciting developments in computational neuroscience, providing tools essential for our modern understanding of the computational principles that govern the development, structure, physiology, and dynamics of the nervous system. In this Special Issue, we aim to bring together neuronal models and neuronal plasticity mechanisms that are grounded in information theory principles, modern inference, and learning algorithms. We welcome submissions that use information theory as the basis for defining generative principles of neuronal dynamics over multiple spatio-temporal scales, which informs our understanding of information processing in the brain. ============================= Dr. Dimitrije Markovic Post-Doc at Technische Universität Dresden, Department of Psychology, Dresden, Germany Lab website: https://tu-dresden.de/mn/psychologie/ifap/ni Phone: +49-351-463-43146 Personal website: http://dimarkov.github.io/ =============================

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PostDoc position University of Minnesota
by Alexander Opitz Sept. 9, 2019

Sept. 9, 2019

A postdoc position funded by the NIH Brain Initiative is available in the lab of Alexander Opitz in the Department of Biomedical Engineering at the University of Minnesota. The lab works in the field of noninvasive brain stimulation across multiple levels of investigation. The candidate will develop and extend existing computational models to bridge physical and physiological effects of transcranial magnetic stimulation (TMS). The candidate will further contribute to analyzing invasive electrophysiological data from NHPs stimulated with TMS. Access to computing resources from the Minnesota Supercomputing Institute are available. The Opitz lab is committed to the career advancement of its members. We offer a diverseand inclusive environment with numerous opportunities for members to develop their own projects and support for fellowships and career development awards. The funded project involves collaborators in New York and Germany and research exchanges will be part of the project. Experienced candidates can be hired at the research associate level. *Qualifications* Required Qualifications: ·Ph.D. in Engineering, Neuroscience, Physics, Applied Mathematics or similarly related field. ·Strong record of technical capabilities in research. ·Expertise in Python/Matlab or other programing languages Preferred Qualifications: ·Experience in computational neuroscience ·Background in computational modeling/analysis of neural data Informal inquiries can be made to aopitz(a)umn.edu. Further details can be found at http://opitzlab.umn.edu/join_us

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NEURON course at SFN 2019 meeting
by Carnevale, Nicholas Sept. 9, 2019

Sept. 9, 2019

Space is still available for the NEURON course at this year's meeting of the Society for Neuroscience, but you'll have to act quickly because the registration deadline is Friday, October 4--less than a month from today. This one-day course is for you, whether you're a PI trying to decide whether to add computational modeling to your research program, a grad student or postdoc just getting started in modeling, or an established NEURON user who wants to find out what the latest advances are. It starts with a practical introduction that reviews basic concepts and presents a workflow for building and working with models of cells and networks, and moves on to topics that include using Python with NEURON, modeling reactive diffusion with the RxD class, and running simulations on parallel hardware from multicore Macs and PCs to massively parallel supercomputers. For more information and the registration form, see https://neuron.yale.edu/neuron/static/courses/chi2019/chi2019.html

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Recruiting two postdocs (UCL, London, UK)
by Love, Bradley Sept. 7, 2019

Sept. 7, 2019

Hello, My lab (bradlove.org<http://bradlove.org>) is searching for two postdocs in computational cognitive neuroscience to work at UCL in London, UK. We are open and supportive of people coming from either the psych/neuro or the computer science side. One push is making deep learning more human-like using brain and behavioral data. Please apply here by 4-October, https://t.co/XcKISJVhp8?amp=1 ******************************** Bradley C. Love University College London b.love(a)ucl.ac.uk<mailto:b.love@ucl.ac.uk> http://bradlove.org<http://bradlove.org/> ********************************

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CFP: FLAIRS 2020, N Miami Beach, Neural Network and Data Mining Special Tracks
by David B Sept. 6, 2019

Sept. 6, 2019

CALL FOR PAPERS FLAIRS 2020, Florida Artificial Intelligence Research Symposium Special Tracks on Neural Networks and Data Mining North Miami Beach, FL https://www.flairs-33.info/ May 17 - 20, 2020 Paper submission deadline: November 18, 2019. Notifications: January 20, 2020. Camera ready version due: February 24, 2020. FLAIRS is a medium-sized interdisciplinary AI conference which especially encourages novel ideas. It features a strong international following, a double-blind review process, free tutorials, and a great venue. Neural Network Track: The special track will be devoted to Neural Networks with the aim of presenting new and important contributions in this area. The areas include, but are not limited to, the following: applications such as Pattern Recognition, Control and Process Monitoring, Biomedical Applications, Robotics, Text Mining, Diagnostic Problems, Telecommunications, Power Systems, Signal Processing; 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 Logic; pre- or post-processing techniques such as feature extraction; or any other area of Neural Network research which is related to artificial intelligence. Papers dealing with tool suites are also encouraged. Data Mining Track This special track will be devoted to data mining with the aim of presenting new and important contributions in this area. Papers and contributions are encouraged for any work related to Data Mining. Topics of interest may include (but are in no way limited to): 1. Applications 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. 2. 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. 3. Feature extraction and selection. 4. Post-processing techniques such as visualization, summarization, or trending. 5. Preprocessing and data reduction. 6. Knowledge engineering or warehousing. Papers dealing with Cloud-based unstructured data or Cloud-based tool suites are also encouraged. Note: We invite original papers (i.e. work not previously submitted, in submission, or to be submitted to another conference during the reviewing process). Submission Guidelines Interested authors should format their papers according to AAAI formatting guidelines. The papers should be original work (i.e., not submitted, in submission, or submitted to another conference while in review). Papers should not exceed 6 pages (or 4 pages for short paper, to be presented as a poster) and are due by November 18. FLAIRS uses a double blind reviewing process. Author names and affiliations should be X’d out on submitted papers. Papers must be submitted as PDF through the EasyChair conference system, which can be accessed through the main conference web site (https://www.flairs-33.info/) Note: do not use a fake name for your EasyChair login - your EasyChair account information is hidden from reviewers. Authors should indicate which special track they are submitting to. The proceedings of FLAIRS will be published by the AAAI. Authors of accepted papers will be required to sign a form transferring copyright of their contribution to AAAI. FLAIRS requires that there be at least one full author registration per paper.

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AICAS2020 - Call for Tutorial Proposals
by Elisa Donati Sept. 6, 2019

Sept. 6, 2019

AICAS 2020 - CALL FOR TUTORIAL PROPOSALS 2nd IEEE Conf. on Artificial Intelligence Circuits and Systems 23th-25th March, 2020, Genova, Italy www.aicas2020.eu <http://www.aicas2020.eu/> Deadline for proposals: November 10th, 2019 https://aicas2020.eu/submissions <https://aicas2020.eu/submissions> The objective of the AICAS 2020 Tutorial Program is to provide participants with an inspiring and informative selection of tutorials that reflect current topics in AI circuits and systems related research and development. Tutorials will cover a one to three-hour period with ten minutes at the end for questions. They will be held in the morning before the technical sessions. We encourage submissions of tutorial proposals on the topics including but not limited to: Circuits and systems for AI Deep learning/machine learning/AI algorithms Tools/Platforms for AI Architecture for AI computing Edge and cloud AI computing platforms Hardware accelerators Neuromorphic processors and computing Hardware/software co-design and design automation for AI systems Advanced neural network design Emerging applications: Deep learning for Internet-of-Things Emerging applications of AI: Medical AI Emerging applications of AI: Autonomous Vehicle Emerging applications of AI: Smart Factory and Environment Emerging applications of AI: Robotics Prospective organizers of tutorial program should submit proposals to the Tutorial Chair indicating: Title of the tutorial, Area of the tutorial (refer to the above topics), Presenter(s) and their CV, Target audience and prerequisite knowledge of audience, 300 words abstract (for inclusion on webpage and in registration materials), Full description (1-2 pages to be used for evaluation),Keywords, Detailed contact information of all presenters (and indication of the main contact person). Contact tutorial chair, email: tutorials(a)aicas2020.eu <mailto:tutorials@aicas2020.eu> PhD. Elisa Donati Institute of Neuroinformatics University and ETH Zurich Winterthurerstrasse 190, 8057 Zurich E-mail: elisa(a)ini.uzh.ch Phone: +41 0446353061

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Call for Papers: AICAS2020 IEEE International Conference on Artificial Intelligence Circuits and Systems
by Elisa Donati Sept. 6, 2019

Sept. 6, 2019

******************************************************************************************************************************************************************** Call for Papers: AICAS2020 IEEE International Conference on Artificial Intelligence Circuits and Systems Conference website: www.aicas2020.eu <http://www.aicas2020.eu/> Submission deadline: September 30, 23:59 (GMT -0700) Submit at: https://epapers.org/aicas2020/ESR/login.php <https://epapers.org/aicas2020/ESR/login.php> Contact: info(a)aicas2020.eu <mailto:info@aicas2020.eu> The theme of AICAS2020 is “Circuits and systems for efficient embedded AI”, revolving around the development of hardware and computational strategies towards an increase in system efficiency that supports efficient, embedded, smart applications (such as mobile, robotics, automotive). Potential topics include but are not limited to: Emerging devices and materials for AI Mixed-signal and in-memory hardware accelerators Digital hardware accelerators Edge AI computing platforms and systems Cloud AI computing platforms and systems Neuromorphic/bioinspired circuits, processors and systems and their applications Hardware/software co-design and design automation for AI systems Deep learning/machine learning/AI algorithms Smart sensors and actuators AICAS in IoT, HCI, healthcare, autonomous systems, homes/factories/cities/nature Tools, libraries, benchmarking for AI Other areas in AI circuits and systems Live demos (1 page papers) Special sessions (invited papers) We invite you to submit papers in the AICAS2020 format. Online submissions will be accepted via ePapers in PDF format (https://epapers.org/aicas2020/ESR/login.php <https://epapers.org/aicas2020/ESR/login.php>). Regular and Special Session Papers length is maximum 4 pages, plus up to 1 page for references (ONLY) or maximum 1 page for Live demos. Please refer to the detailed information for authors. Papers will comply with IEEE conference template and camera ready manuscripts will be checked for IEEExplore compliance. The review process is double-blind. Authors of selected best papers will be invited to submit extended versions of their work for publication in IEEE JETCAS special issue. On Behalf of the Conference Organizing Committee, Chiara Bartolozzi - Istituto Italiano di Tecnologia (Italy), Shih-Chii Liu - University of Zurich and ETH (Switzerland), Tobi Delbruck - University of Zurich and ETH (Switzerland), Marian Verhelst - KU Leuven (Belgium) and Maurizio Valle - University of Genova (Italy) PhD. Elisa Donati Institute of Neuroinformatics University and ETH Zurich Winterthurerstrasse 190, 8057 Zurich E-mail: elisa(a)ini.uzh.ch Phone: +41 0446353061

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