- Comp-neuro - lists.cnsorg.org

Postdoctoral Research Fellow roles - EPSRC Centre for Predictive Modelling in Healthcare, University of Exeter
by Purcell, Sarah Aug. 13, 2018

Aug. 13, 2018

2 Postdoctoral Research Fellow roles - EPSRC Centre for Predictive Modelling in Healthcare University of Exeter, UK Two Research Fellows are required to support the EPSRC Centre for Predictive Modelling in Healthcare<http://emps.exeter.ac.uk/mathematics/research/pmh/> (CPMH). The roles are available from 01 October 2018, or a mutually agreeable date soon thereafter, for a period of up to 24 months. The CPMH is a £2M award which brings together outstanding scientists from mathematics, statistics, computer science and our medical school. With an additional £7M in research funding, the interface between mathematics, computer science and healthcare is one of the most rapidly expanding areas within the University. The Centre forms part of the Quantitative Biology and Medicine Initiative, which currently consists of 15 PDRAs, 9 fellowship holders, and 10 PhD students. The successful candidates are expected to focus on one of the following areas, depending on their interests and background: (a) Transient dynamics of networks with multiple time scales: there are significant mathematical challenges from disease modelling that require the development of new techniques to understand transient behaviour in multiple timescale systems, especially for systems where there is not a simple factorization into fast and slow subsystems. (b) Numerical investigation of models of cardiac diseases: involving multi-scale excitable and transient dynamics, with a focus on re-entrant arrhythmias specifically concerning development and improvements of antiarrhythmia pacing, low-voltage defibrillation and catheter ablation. [In partnership with cardiologists at the RD&E Hospital, Exeter]. (c) Mathematical modelling and analysis of EEG in dementia: EEG analysis has shown promise in differentiating people with dementia from healthy older adults, and therefore could provide indications for early diagnosis. We will use mathematical models to better understand why differences in EEG occur and combine models and analysis to build improved diagnostic markers. [In partnership with colleagues in Bath, Bristol & Reading]. (d) Mathematical modelling and analysis of polygenic disease: conditions such as diabetes and dementia depend on the simultaneous presence of several genes; they are not inherited as simply as single-gene diseases and therefore require the development of new mathematical approaches to improve diagnosis via e.g. the interpretation and uncertainty quantification of proportions of patients in large data sets (e.g. UK Biobank) using genetic risk scores. [In partnership with diabetologists and neurologists from the Medical School]. For full details please see the job advert<https://www.jobs.ac.uk/job/BLL261/postdoctoral-research-fellow/>. Application deadline: 20 August 2018. For further information please contact Centre Manager Sarah Purcell, email S.Purcell(a)exeter.ac.uk<mailto:S.Purcell@exeter.ac.uk> or telephone 01392 726447.

1 0

PhD deeplearning in neuroimaging - Amsterdam
by Rajat Thomas Aug. 10, 2018

Aug. 10, 2018

PhD student “Deep learning analysis of neuroimaging data” The job Amsterdam UMC (University of Amsterdam) has a vacancy for a PhD student. The aim of the project is to develop deep neural network (DNN) analysis of neuroimaging data to enable neuroimaging biomarker development. Neuroimaging data consist of thousands of features but the training of DNNs is typically hampered by limited samples. You will use large existing datasets (>10.000 subjects) for the development of DNN analysis and test the resulting models in smaller samples to develop neuroimaging biomarkers for psychiatric disorders. Our department The project is a collaboration with Phillips Research and funded by a public-private partnership grant from the Netherlands Organisation for Scientific Research (NWO). You will closely collaborate with experts in DNN and neuroimaging data analysis from Philips. The project is embedded within the Department of Psychiatry of the Amsterdam UMC, and you will be supervised by Dr. Rajat Thomas (deep learning) and Prof. Guido van Wingen (neuroimaging). Your experience We are looking for a highly talented and dedicated PhD student with a (nearly completed) Master’s degree in a computer science, artificial intelligence, bioinformatics, mathematics, statistics, engineering, or related discipline. You have a strong background in mathematics, statistics, and programming, preferably in one of the major frameworks for deep learning like TensorFlow, Pytorch and/or Keras, and preferably have experience with medical image analysis. You have good communicative skills and are well able to work independently as well as in a team. You are proficient in English in speech and writing. Dutch is a plus but not required. Our offer We offer a challenging research project and excellent resources for the duration of 4 years. The starting date is preferably around December 2018. Compensation is according to the collective agreement (CAO-UMC), and amounts from EUR 2.279,- gross per month in the first year to EUR 2.919,- in the fourth year. You will be employed by AMC Medical Research BV. Your application For more information, please contact Dr. Rajat Thomas (r.m.thomas(a)amc.nl) or Prof. Guido van Wingen (g.a.vanwingen(a)amc.nl) Please apply online before September 8 at https://werkenbijamc.nl/vacatures/phd-student-deep-learning-analysis-of-neu…

1 0

Postdoc deeplearning in medical imaging - Amsterdam
by Rajat Thomas Aug. 10, 2018

Aug. 10, 2018

Postdoctoral / Ph.D. researcher “Deep learning analysis of neuroimaging data” The job Amsterdam UMC (University of Amsterdam) has a vacancy for a postdoctoral researcher. The aim of the project is to develop deep neural network (DNN) analysis of neuroimaging data to enable neuroimaging biomarker development. Neuroimaging data consist of thousands of features but the training of DNNs is typically hampered by limited samples. You will use large existing datasets (>10.000 subjects) for the development of DNN analysis and test the resulting models in smaller samples to develop neuroimaging biomarkers for psychiatric disorders. Our department The project is a collaboration with Phillips Research and funded by a public-private partnership grant from the Netherlands Organisation for Scientific Research (NWO). You will closely collaborate with experts in DNN and neuroimaging data analysis from Philips. The project is embedded within the Department of Psychiatry of the Amsterdam UMC, and you will be supervised by Dr. Rajat Thomas (deep learning) and Prof. Guido van Wingen (neuroimaging). Your experience We are looking for a postdoctoral fellow with a (nearly completed) PhD in computer science, artificial intelligence, bioinformatics, mathematics, statistics, engineering, or related discipline. You have a strong background in mathematics, statistics, and programming in one of the major frameworks for deep learning like TensorFlow, Pytorch and/or Keras, and preferably have experience with medical image analysis. You have excellent communicative skills in written and spoken English (Dutch is a plus but not required) and are well able to work independently as well as in a team. You have an interest in neuroscience and developing biomedical applications, and as postdoctoral researcher will assist in the supervision of junior researchers. Our offer We offer a challenging research project and excellent resources for the duration of 1 year with a possible extension of 2 years. The starting date is preferably around December 2018. Compensation is according to the collective agreement (CAO-UMC), depending on education and experience. You will be employed by AMC Medical Research BV. Your application For more information, please contact Dr. Rajat Thomas (r.m.thomas(a)amc.nl) or Prof. Guido van Wingen (g.a.vanwingen(a)amc.nl) Please apply online at https://werkenbijamc.nl/vacatures/postdoctoral-researcher-deep-learning-ana…

1 0

ESI SyNC Conference 2018 - Integrative Mechanisms of Cognitive Neuroscience | DEADLINE APPROACHING
by André Castro Aug. 9, 2018

Aug. 9, 2018

Dear all, this is a kind reminder that ESI Sync 2018 is approaching. The registration deadline is 15th August and only a limited number of places are available. This year’s theme is "Integrative Mechanisms in Cognitive Neuroscience: Crossroads to the Brain”. The conference will begin in the morning of 30th August and end in the evening of 31st August 2018 at the Ernst Strüngmann Institute in Frankfurt, Germany. Our confirmed invited speakers are the following: - David Melcher (University of Trento, Italy) -- "Temporal rhythms of visual perception" - Dimitri Kullmann (UCL, UK) -- "Hippocampal gamma oscillations: dynamical properties and closed-loop manipulation" - Matteo Carandini (UCL, UK) -- "Local and global neural correlates of vision, action, and reward" - Biyu He (NYU, US) -- ''Large-scale brain dynamics underlying visual perceptual awareness'' - Tobias Donner (UKE, Germany) -- tba - Wim Vanduffel (KU Leuven, Belgium) -- "Optogenetic interrogation of the attention network in primates" - Anitha Pasupathy (University of Washington, US) -- "Encoding things and stuff: multiplexed form and texture signals in primate V4" - Floris de Lange (Radboud University, Netherlands) -- "How do prior expectations influence sensory computations?" - Hannah Monyer (Heidelberg University, Germany) -- ''GABAergic neurons – the cellular substrate for local and long-range synchrony'' - James Bisley (UCLA, US) -- ''The complementary roles of areas LIP and FEF in guiding eye movements'' This year we have the pleasure to announce as our special guest the choreographer Ildikó Tóth! In order to register, please fill out the registration form (that can be found at http://www.esi-frankfurt.de/registration/ ) and email it to events(a)esi-frankfurt.de. Please see our [website](http://www.esi-frankfurt.de/esisync/esisync-home/) for more details and updates on the programme. Organising Committee: Wolf Singer Pascal Fries André Castro Tommaso Tosato Ana Broggini Miriam Mueller Renata Vajda

1 0

Final call and reminder - workshop on Computational Neuroscience and Robotics: University of York, 3-5 Sep 2018.
by David Halliday Aug. 8, 2018

Aug. 8, 2018

The SPANNER workshop on Astrocyte-Neuron interactions, Spiking Neural Networks and Autonomous robotics is still accepting applications to attend. Due to sponsorship we can offer free registration, including meals at this 2.5 day workshop. We have invited speakers from USA, EU and UK. We are still accepting abstracts for contributed talks. Overnight accommodation will be provided for PhD students and early career researchers and PhD student travel bursaries are available. Up to date information is on the web site: https://www.york.ac.uk/spanner-workshop We warmly invite you to the historic city of York next month.

1 0

PhD positions in CRC 1330 Hearing Acoustics
by Seeber, Bernhard Aug. 7, 2018

Aug. 7, 2018

Dear colleagues, on behalf of Dr. Ewert I am pleased to announce two open positions in the Medical Physics Group at the University of Oldenburg, Germany, funded by the Deutsche Forschungsgemeinschaft (DFG) as part of newly established collaborative research centre CRC1330 Hearing Acoustics. Further information can be found here: PhD Position in the area of of auditory-object-based perception modelling for complex scenes: https://www.uni-oldenburg.de/stellen/?stelle=66162 PhD Position in the area of psychoacoustics in complex audio-visual virtual environments: https://www.uni-oldenburg.de/stellen/?stelle=66163 Both projects aim to transition from classical lab testing of hearing with simplified stimuli to using life-like realistic scenarios. Applications are requested no later than August 31, 2018. Many thanks, Stephan Ewert (Bernhard Seeber)

1 0

Extension Call for Abstracts: New Deadline August 31 - Cognitive Computing - Merging Concepts with Hardware
by Prof. Dr. Gordon Pipa Aug. 6, 2018

Aug. 6, 2018

Upon demand and the holiday period in August we extend the Deadline for submissions of abstracts until the end of August. New Deadline for Abstract submission: August 31 Call for participation and contributions: COGNITIVE COMPUTING: MERGING CONCEPTS WITH HARDWARE December 18-20, 2018, Hannover, Germany http://www.cognitive-comp.org/ ** An interdisciplinary networking event / scientific conference ** We would like to draw your attention to an upcoming scientific community event. The aim of this conference is to work towards a general, productive, and rigorous theory of “computing” in non-digital, nonlinear physical substrates. Biological brains and unconventional computing machines would become understandable as different instantiations of the same underlying principles. Three scientific communities, namely - cognitive and computational neurosciences, - theory of computation, and - nonlinear materials, devices and systems have since long been exploring diverse facets of such principles of non-digital computing. But differences in terminology, discipline-specific objectives and a scattered spectrum of formal methods have handicapped cross-fertilization. Everything in this conference is geared toward stimulating linkages between these fields: - single-track with few but rather long oral presentations, - long break and poster session times for person-to-person interaction, - keynote and plenary speakers with interdisciplinary renown, - a limited (200) number of participants, - a splendid setting in the Castle of Herrenhausen, a heritage of the Kings of Hannover, with adjoining hectares of classical French gardening. Invited and confirmed speakers: - Kwabena Boahen, Stanford University - Joanna J. Bryson, Univ. of Bath and Princeton University - Chris Eliasmith, University of Waterloo - Edward A. Lee, UC Berkeley - Demetri Psaltis, EPFL Lausanne - Pieter Roelfsema, Vrije Universiteit Amsterdam & Netherlands Institute for Neuroscience - Susan Stepney, University of York - Ipke Wachsmuth, University of Bielefeld - David Wolpert, Santa Fe Institute We solicit the submission of 2-page abstracts, with themes oriented toward our five topical sessions: - applications of unconventional computing systems, - theoretical concepts and mathematical foundations, - neuromorphic hardware, - novel physical substrates, - guides from neuroscience for computing technologies. In addition to latest specific achievements, we specifically encourage survey / introductory / didactic contributions. Detailed information can be found on http://www.cognitive-comp.org/ and in the Call for Abstracts that is posted there. Timelines: - Abstract submission: July 31 - Notification of acceptance: September 30 - Final abstract for online publication: October 31 Registration fees: - Students (incl. PhD students): 150 Euro - Others (academic): 300 Euro - Industry: 900 Euro Contributors of accepted oral presentations will be exempted from fees and will receive travel refunding. The event was made possible by the generous support from the Volkswagen Foundation, Germany’s largest private organization for the advancement of scientific research. The organizers: - Daniel Brunner (photonics, neuromorphic architectures; CNRS / University of Burgundy - Franche-Comté) - Herbert Jaeger (machine learning, nonlinear dynamics; Jacobs University Bremen) - Stuart Parkin (nano systems, quantum electronic materials; Max-Planck-Institute for Microstructure Physics, Halle) - Gordon Pipa (neuroinformatics and cognitive computing; University of Osnabrück)

1 0

One postdoc and two PhD positions in Emmy-Noether group "Decision Neuroscience of Human Cooperation" in Hamburg, Germany
by Christoph Korn Aug. 3, 2018

Aug. 3, 2018

Dear all, I would be very grateful, if you could circulate the following job announcements. One postdoc and two PhD positions are available within the newly funded Emmy-Noether research group "Decision Neuroscience of Human Cooperation" led by Christoph Korn. *Research topic and group:* The group's aim is to investigate the decision-making and learning processes relevant for successful social cooperation between humans. The planned projects rely on a variety of theoretical and methodological approaches including computational modeling of behavioral data, evolutionary game theory, model-based and multivariate analyses of fMRI data, pupillometry, virtual reality, and testing of psychiatric patients. The group is based at the Institute of Systems Neuroscience (head: Prof. Christian Büchel) at the University Medical Center Hamburg-Eppendorf in Hamburg, Germany. Psychiatric patients are tested in collaboration with Sabine Herpertz and her lab at the Heidelberg University Hospital. You can find more information here: http://christoph-korn.net/ *What the group offers:* - Opportunity to get hands-on supervision for learning various data acquisition and analysis techniques - Dynamic, interdisciplinary, and international research environment within the Institute of Systems Neuroscience - Research-dedicated T3 MR scanner (PRISMA), eye-tracking and VR laboratories, excellent infrastructure for behavioral testing - Multiple training opportunities within the institute (e.g., https://goo.gl/pU44vP) - Possibility to join the local graduate school, which is a member of national and international networks - Possibility of research stay with collaboration partners in the US *Your profile:* - You are interested in investigating how cooperation, decision-making, and learning relate to human brain activity and how they go awry in psychiatric disorders. - You like to design experiments, devise models, and analyze various types of data. - You have experience in conducting and analyzing behavioral experiments with human participants. - You are fluent in English. For the postdoc position and for one of the PhD positions, knowledge of German is not necessary. *Requirements for the postdoc position:* - A PhD (completed or close to the completion) in neuroscience, cognitive science, psychology, economics, medicine, or a related discipline. - Experience in conducting and analyzing neuroimaging experiments (including familiarity with SPM, FSL, or similar programs). - Experience in using programming languages such as Matlab, R, or Python. - Experience in writing and publishing peer reviewed scientific papers. *Requirements for the PhD positions:* - A Master of Science or an equivalent degree in neuroscience, cognitive science, psychology, economics, medicine, or a related discipline. - Experience in programming and in conducting or analyzing neuroimaging experiments is a big plus. - One of the PhD candidates will be (partly) based in Heidelberg to test psychiatric patients. This position is ideal for applicants with an interest in clinical psychiatry and requires knowledge of German to interact with patients. *Application and job specifications:* Applications will be accepted until the positions are filled. The first review of applications will be in the beginning of September 2018. Preferred starting date is January 2019 but later starting dates may be possible. Salary depends on experience and is based on German regulations (the postdoc position is remunerated with the factor 100%, the PhD positions with the factor 65%). The appointments will be initially for 3 years with the possibility for continuation. The group is committed to maintaining a diverse and inclusive environment. If you are interested, please send one pdf-document including your CV, a brief statement of research interest, and the contact details of two academic referees to *c.korn(a)uke.de <c.korn(a)uke.de>*. Informal inquiries are welcome. Looking forward to hearing from you, Christoph

1 0

A biologically motivated and more powerful alternative to locality-sensitive hashing
by Rod Rinkus Aug. 2, 2018

Aug. 2, 2018

I believe this community will be interested in a new downloadable Java app that I 've just made available on my web site (on this page <http://www.sparsey.com/CSA_explainer_app_page.html>), which describes an alternative, biologically motivated/plausible, way to achieve the goals of locality-sensitive hashing (LSH). This alternative model, called Sparsey, achieves a more graded notion of similarity preservation than LSH, and has many other advantages as well. Sparsey has a natural correspondence to the brain's cortex, centering on the idea that all items of information are stored as sparse distributed codes (SDCs), a.k.a., cell assemblies, in superposition in mesoscale cortical modules, e.g., macrocolumns (though other structures, e.g., mushroom bodies, are also candidates). Briefly, Sparsey preserves similarity from input space to SDR code space (measured as intersection size) as follows. - The process of choosing an SDC takes the form of Q independent softmax choices, one in each of the Q WTA competitive modules (CMs) that comprise the SDR coding field. - The familiarity (inverse novelty) of the input, denoted "G", which is in [0,1], is computed. This is an extremely simple computation. - The amount of noise in those Q softmax choice processes is modulated as a function of G. Basically, the softmax is over the distribution of input summations of the competing cells (in a given CM), but we use G to modulate (i.e. sharpen vs. flatten) those distributions. - When G is near 1 (perfect familiarity), the distributions are greatly sharpened, causing the expected number of CMs in which the cell with the highest input summation wins (and thus, the expected intersection of the resulting SDR with the closest matching previously stored SDR) to increase towards Q. When G is near 0 (completely novel), the distributions are flattened, causing the expected number of CMs in which the cell with max input summation wins (and thus, the expected intersection of the resulting SDR with the closest matching previously stored SDR) to decrease towards chance. In other words, this G-based modulation of the distributions, which can be viewed as varying the amount of noise in the choice process, achieves similarity preservation. I encourage members of this community to explore the app to understand this simple and more powerful alternative to LSH. I welcome your feedback. Sincerely, Rod Rinkus -- Gerard (Rod) Rinkus, PhD President, rod at neurithmicsystems dot com Neurithmic Systems LLC <http://sparsey.com> 275 Grove Street, Suite 2-400 Newton, MA 02466 617-997-6272 Visiting Scientist, Lisman Lab Volen Center for Complex Systems Brandeis University, Waltham, MA grinkus at brandeis dot edu http://people.brandeis.edu/~grinkus/ <http://people.brandeis.edu/%7Egrinkus/>

1 0

Postdoc position in Geometric Methods for Deep and Reinforcement Learning at RIST
by Luigi Malagò Aug. 2, 2018

Aug. 2, 2018

=========================================================== *Subject*: Postdoc position in Machine Learning (1 year, renewable up to 2 years) *Institution*: RIST - Romanian Institute of Science and Technology, Cluj-Napoca *Keywords*: Deep Learning, Reinforcement Learning, Stochastic Optimization, Optimization over Manifolds, Information Geometry, Riemannian Geometry *Application deadline*: 15 August 2018 (applicants are encouraged to apply earlier) *Salary*: around 2200 euro net *Official announcement*: http://rist.ro/en/details/news/postdoc-positio ns-in-deep-learning-and-machine-learning.html =========================================================== Dear colleagues, the Romanian Institute of Science and Technology (RIST) has an opening for a postdoc position, in the context of the DeepRiemann project “Riemannian Optimization Methods for Deep Learning”, funded by European structural funds through the Competitiveness Operational Program (POC 2014-2020). The appointments will be for 1 year, with possible extensions up to 2 years. The DeepRiemann project aims at the design and analysis of novel training algorithms for Neural Networks in Deep Learning, by applying notions of Riemannian optimization and differential geometry. The task of the training a Neural Network is studied by employing tools from Optimization over Manifolds and Information Geometry, by casting the learning process to an optimization problem defined over a statistical manifold, i.e., a set of probability distributions. The project is highly interdisciplinary, with competences spanning from Machine Learning to Optimization, Deep Learning, Statistics, and Differential Geometry. The objectives of the project are multiple and include both theoretical and applied research, together with industrial activities oriented to transfer knowledge, from the institute to a startup or spin-off of the research group. The positions will be part of the new Machine Learning and Optimization group https://rist.ro/en/teams.html, which performs research at the intersection of Machine Learning, Stochastic Optimization, Deep Learning, and Optimization over Manifolds, using geometric methods based on Information Geometry. The group is one of two newly-formed groups in Machine Learning at RIST. The official job announcement can be seen here: http://rist.ro/en/details/news/postdoc-positions-in-deep-lea rning-and-machine-learning.html Informal inquiries can be sent to Dr. Luigi Malagò <malago(a)rist.ro>, principal investigator of the DeepRiemann project. Application deadline: 15 August 2018 (applicants are encouraged to apply earlier) best regards, Luigi Malagò

1 0