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Doctoral student position - Robot-assisted modeling of spatial navigation paradigms in biological organisms - DEADLINE EXTENDED
by samarasinghe＠ini.rub.de Sept. 1, 2017

Sept. 1, 2017

Please note that the deadline for applications to the position below has been extended to *15.09.2017*. *Research **Position **at the Institute for Neural Compu**ta**ti**o**n * A position as *d**octoral student **in integrative **n**euroscience and **c**ognitive **s**cience *is available immediately in the group of Prof. Sen Cheng in the Institute for Neural Computation at the Ruhr University Bochum, Germany. The research will focus on robot-assisted modeling of spatial navigation paradigms in biological organisms. Robotic simulations, as well as, physical robots will be used to develop and evaluate the desired models. The position will be funded at 50% of the standard salary scale TV-L E13. It is initially limited to 1 year with the possibility of extension, depending on the availability of funding. Candidates should have an excellent degree in neuroscience, physics, mathematics, engineering, or a related field. Competence in mathematical modeling, and excellent programming skills (Python, C/C++, or Matlab) are mandatory. Candidates are further required to have a strong background in at least one of the following fields: robotics, computational neuroscience, or cognitive modeling. Experience with interdisciplinary research in integrative neuroscience and cognitive science and with collaborative research would be a further asset. The working language at the institute is English. To apply, please send a statement of your research interests, academic transcripts, and a complete CV in one PDF file to samarasinghe(a)ini.rub.de <mailto:samarasinghe@ini.rub.de> by *15**.09****.2017*. Please also request from at least two academic referees that they send letters of reference directly to the same email address. Further information may be available at https://www.ini.rub.de/the_institute/jobs/. The Ruhr University Bochum provides a dynamic research environment in neuroscience and cognitive science. The Institute for Neural Computation unifies various core competencies extending from experimental and theoretical neuroscience to machine learning and robotics. The Ruhr University Bochum is committed to equal opportunity. We strongly encourage applications from qualified women and persons with disabilities. -- Vinita Samarasinghe M.Sc., M.A. Science Manager Arbeitsgruppe Computational Neuroscience Institut für Neuroinformatik Ruhr-Universität Bochum, NB 3/26 Universitätstr. 150 D-44780 Bochum Tel: +49 (0)234 32 27316 Email: samarasinghe(a)ini.rub.de Hours: Monday 9-12 & 14-16; Friday 9-12 & 14-16; Wednesday 12 - 16

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Postdoc position: computational models of visual memory, Rust lab, UPenn
by Rust, Nicole C Sept. 1, 2017

Sept. 1, 2017

A postdoctoral position focused on developing computational models of visual memory is available in the laboratory of Nicole Rust at the University of Pennsylvania. The lab is broadly interested in understanding the neural processing supporting massive-capacity, single-trial visual memories of images. This specific position involves developing classes of computational models that describe where and how visual memories are stored in the brain as well as how the percept of visual familiarity is signaled. Models include extensions of state-of-the-art descriptions of visual processing (e.g. deep neural networks) as well as more dynamic, mechanistic descriptions. To constrain these models, the researcher will interface with experimentalists in the lab who record and perturb neural signals in monkeys and tree shrews. Opportunities also exist to collaborate with the Simoncelli lab at NYU, the Yamins lab at Stanford, and with other members of the Penn Computational Neuroscience Initiative. Candidates should have a Ph.D. in Computational Neuroscience, Computer Science or a related field prior to starting. The ideal candidate has extensive experience in computational modeling as well as working with behavioral and/or neural data. To inquire about this position, please submit a CV and a brief statement of research interests to nrust(a)psych.upenn.edu<mailto:nrust@psych.upenn.edu>. Nicole Rust Associate Professor Department of Psychology University of Pennsylvania Philadelphia, PA http://www.sas.upenn.edu/psych/rust-lab/

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[EAIS 2018] Paper Submission deadline is on Saturday, 20th of January 2018 2359 UTC-12hr
by Teng Teck Hou Sept. 1, 2017

Sept. 1, 2017

[Apologies for cross-postings] ################################################## CALL FOR PAPERS IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS 2018) 25-27 of May 2018, Island of Rhodes, Greece http://easyconferences.eu/eais2018/ ################################################## Contributions will be selected based upon their quality as evaluated by the reviewers. An online submission system for contributions will be made available on this webpage soon. Papers must be comprised of up to 8 pages and they will be published in the IEEE Explore All contributions have to be prepared according to the IEEE conference style guidelines. To see the Topics please visit: http://easyconferences.eu/eais2018/topics.html ################################################## The 2018 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS 2018) will be held in The 2018 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS 2018) will be held in the exotic island of Rhodes (Greece) which has a beautiful medieval town built by the crusaders and it is preserved as UNESCO monument. A main characteristic of Rhodes is its long ancient history with many ancient Greek sites. Set against the historic backdrop of Rhodes island is the elegant and pisturesque lowrise architecture of Aldemar Amilia Mare Village, an all-inclusive seaside resort. Newly refurbished luxury rooms with sea or garden views are the perfect choice for all holidaymakers, f rom singles to families. Dive into crystal clear swimming pools, try a wide range of watersports at the beach, enjoy the Spa Centre with its fully equipped fitness area and sample the cosmopolitan delights of the themed restaurants. ##############################Important Dates############################## * Paper Submission January 20, 2018 * Special Session Proposals 20 December, 2017 * Paper Decision Notification January 15, 2018 * Camera-Ready Submission February 15, 2018 * Authors registration To be announced * Conference May 25 - 27 2018 ########################################################################### ########################## At least three distinguished Keynote Speakers will be invited ########################## ##################### SPECIAL ISSUES ################################### Selected papers (from the list of the accepted and presented ones) will be considered for publication and inclusion in Special Issue of the EVOLVING SYSTEMS (EVOS) Springer Journal. At least one more Special Issue will be edited ##################Topics and Areas of Interest################## This conference solicits papers addressing original works in topics and areas of interest including, but are not limited to: * Basic Methologies Evolving Soft Computing Techniques Evolving Fuzzy Systems Evolving Rule-Based Classifiers Evolving Neuro-Fuzzy Systems Adaptive Evolving Neural Networks Adaptive Evolving Fuzzy Systems Online Genetic and Evolutionary Algorithms Data Stream Mining Incremental and Evolving Clustering Approaches Adaptive Control Adaptive Pattern Recognition Computational Intelligence in Control and Estimation Incremental and Evolving ML Classifiers Adaptive Statistical Techniques Evolving Decision Systems Big Data Advanced Concepts * Problems and Methodologies in Data Streams Stability, Robustness, Convergence in Evolving Systems Online Feature Selection and Dimension Reduction Online Active and Semi-supervised Learning Online Complexity Reduction Computational Aspects Interpretability Issues Incremental Adaptive Ensemble Methods Online Bagging and Boosting Self-monitoring Evolving Systems Human-Machine Interaction Issues Hybrid Modeling Transfer Learning Reservoir Computing Real-world Applications * EIS for On-Line Modeling, System Identification, and Control EIS for Time Series Prediction EIS for Data Stream Mining and Adaptive Knowledge Discovery EIS in Robotics, Intelligent Transport and Advanced Manufacturing EIS in Advanced Communications and Multi-Media Applications EIS in Bioinformatics and Medicine EIS in Online Quality Control and Fault Diagnosis EIS in Condition Monitoring Systems EIS in Adaptive Evolving Controller Design EIS in User Activities Recognition EIS in Huge Database and Web Mining EIS in Visual Inspection and Image Classification EIS in Image Processing EIS in Cloud Computing EIS in Multiple Sensor Networks EIS in Query Systems and Social Networks EIS in Alternative Statistical and Machine Learning Approaches ################################################################ ##########################Organizing Committee########################## * General co-Chairs Plamen Angelov, Lancaster University, UK Yannis Manolopoulos, Aristotle University of Thessaloniki, Greece PC co-Chairs Edwin Lughofer Johannes, Kepler University Linz, Austria Lazaros Iliadis, Democritus University of Thrace Honorary co-Chairs Dimitar Filev, Ford Motor Company, USA Nikola Kasabov, Auckland University of Technology, New Zealand Special session co-Chairs Abdelhamid Bouchachia, University of Bournemouth, UK Jose Antonio Iglesias, Carlos III University of Madrid (Leganes, Spain) Organizing Chair Apostolos Papadopoulos, Aristotle University of Thessaloniki, Greece Local Organizing co-Chairs Constantinos Demertzis, Democritus University of Thrace, Greece Antonis Papaleonidas, Democritus University of Thrace, Greece Workshop co-chairs M. Sayed - Mouchaweich, Universite Lille, France Andre Paim Lemos, Univerity Minas Gerais, Brazil Publicity and Publication co-Chairs Teck-Hou, Teng Singapore Management University, Singapore Antonis Papaleonidas, Democritus University of Thrace, Greece Web Admin Kyriakos Georgiades, Easy Conferences, Cyprus * International Program Committe Plamen Angelov, Lancaster University, UK Rosangela Ballini, University of Campinas, Brazil Jorge Cassillas, University of Granada, Spain Dejan Dovzan, University of Ljubljana, Slovenia Nadine Gaertner, SAP, Germany Lazaros Iliadis, Democritus University of Thrace, Greece Nik Kasabov, Auckland University of Technology, New Zealand Spyros Likothanasis, University of Patras, Greece Daniel Furtado Leite, Federal University of Lavras, Brazil Andre Lemos, Federal University of Minas Gerais, Brazil Edwin Lughofer, Johannes Kepler University, Linz, Austria Yannis Manolopoulos, Aristotle University of Thessalonii, Greece Trevor Martin, University of Bristol, UK Seiichi Ozawa, Kobe University, Japan Witold Pedrycz, University of Alberta, Canada Radu-Emil Precup, University of Timisoara, Romania Olga Senyukova, Lomonosov Moscow State University, Moscow, Russia El Mustapha Mouaddib, Universite de Picardie Jules Verne, France Jus Kocijan, Jozef Stefan Institute, Ljubljana,Slovenia ####################################################################### #########################Sponsoring Organizations######################### * IEEE * Aristotle University of Thessaloniki, Greece * Democritus University of thrace, Greece ##########################################################################

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Penn Psych - Faculty Search
by Rust, Nicole C Aug. 29, 2017

Aug. 29, 2017

Assistant Professor, Cognitive or Affective Science Department of Psychology, University of Pennsylvania The Department of Psychology at the University of Pennsylvania intends to make multiple appointments in the areas of Cognitive Science and Affective Science over the next several years. Our primary focus is at the junior, Assistant Professor level, but in exceptional circumstances a more senior hire may be considered. We are interested in candidates with research interests in the areas, broadly defined, of cognitive science (e.g., learning and memory, perception, attention, language, or decision making) or affective science (e.g., clinical or health psychology; social, moral, or political psychology; positive psychology; or the psychology of individual differences), and who use any number of approaches, including but not limited to computational, neuroscientific (behavioral, systems, or cognitive), or developmental. Interested candidates should submit materials online at http://facultysearches.provost.upenn.edu/postings/1121 and include a curriculum vitae, statements of research and teaching interests, and the names and contact information of three referees. Candidates will contribute to the teaching mission of the university with introductory courses such as Introduction to Psychology, Introduction to Brain and Behavior, Cognitive Psychology, or Abnormal Psychology, as well as advanced undergraduate or graduate courses in specific areas of interest. Referees will be contacted by the University with instructions on how to submit a recommendation letter to the website. Review of applications will begin on September 18, 2017 and continue until the position is filled. The Department of Psychology is strongly committed to Penn’s Action Plan for Faculty Diversity and Excellence and to creating a more diverse faculty (for more information, see http://www.upenn.edu/almanac/volumes/v58/n02/diversityplan.html) The University of Pennsylvania is an equal opportunity employer. Minorities, women, individuals with disabilities, and protected veterans are encouraged to apply. Nicole Rust, Ph.D. Associate Professor Department of Psychology University of Pennsylvania Philadelphia, PA 19104 http://www.sas.upenn.edu/psych/rust-lab/

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[jobs] Researcher in Cognitive Robotics
by Di Nuovo, Alessandro Aug. 29, 2017

Aug. 29, 2017

Apologies for multiple postings. A fixed-term position is available at Sheffield Hallam University (UK), within Sheffield Robotics. The post is funded by the EPSRC project EP/P030033/1 - Number Understanding Modelling in Behavioural Embodied Robotic Systems (NUMBERS). Details of the post and the link for applying can be found here: http://www.jobs.ac.uk/job/BDR925/researcher-cognitive-robotics/ NUMBERS is a highly inter-disciplinary cutting-edge cognitive robotics research programme lead by Dr Alessandro Di Nuovo and developed in collaboration with Sheffield Robotics. The project sees the participation of Plymouth University and Stanford University (USA), and received the support of the NVIDIA Corporation (USA). It will utilise one of the most advanced child-like robotic platforms (the "iCub") to construct a novel artificial cognitive model of mathematical cognition by imitating human like learning approaches for developing number understanding. The researcher will contribute to the project by carrying out experiments with the iCub, including: Software development. Collecting and analysing data. Guaranteeing continuity of the robotic experiments. The researcher will also be an active member of the Sheffield Robotics team contributing to scientific publications and supporting exhibitions and demonstrations. Experience of working with the iCub robotic platform would be an advantage as well as the knowledge of deep learning software frameworks. This is an exciting opportunity to contribute to the development of the next generation of socially interactive robots capable of learning and mimicking advanced capabilities of human intelligence. Contact e-mail: a.dinuovo(a)shu.ac.uk

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[Extended Deadline-CFP] - HAI 2017 Workshop: Representation Learning for Human and Robot Cognition
by Amir Aly Aug. 28, 2017

Aug. 28, 2017

CALL FOR PAPERS **Apologies for cross posting ** The full day workshop: "*Representation Learning for Human and Robot Cognition*" In conjunction with the *5th International Conference on Human-Agent Interaction* *- Bielefeld - Germany - October * *17th, 2017* *Webpage: **http://cognitive-mirroring.org/en/events/hai2017_workshop/* <http://cognitive-mirroring.org/en/events/hai2017_workshop/> *I. Aim and Scope *Creating intelligent and interactive robots has been subject to extensive research studies. They are rapidly moving to the center of human environment so that they collaborate with human users in different applications, which requires high-level cognitive functions so as to allow them to understand and learn from human behavior. To this end, an important challenge that attracts much attention in cognitive science and artificial intelligence, is the “Symbol Emergence” problem, which investigates the bottom-up development of symbols through social interaction. This research line employs representation learning based models for understanding language and action in a developmentally plausible manner so as to make robots able to behave appropriately on their own. This could open the door to robots to understand syntactic formalisms and semantic references of human speech, and to associate language knowledge to perceptual knowledge so as to successfully collaborate with human users in space. Another interesting approach to study representation learning is “Cognitive Mirroring”, which refers to artificial systems that could make cognitive processes observable, such as the models that could learn concepts of objects, actions, and/or emotions from humans through interaction. A key idea of this approach is that robots learn individual characteristics of human cognition rather than acquiring a general representation of cognition. In this way, the characteristics of human cognition become observable and can be measured as modifications in model parameters, which is difficult to verify through neuroscience studies only. In this workshop, we invite researchers in artificial intelligence, cognitive science, cognitive robotics, and neuroscience to share their knowledge and research findings on representation learning, and to engage in cutting-edge discussions with other experienced researchers so as to help promoting this research line in the Human-Agent Interaction (HAI) community. *II. Keynote Speakers * 1. *Beata Joanna Grzyb *– Radboud University – The Netherlands 2. *Thomas Hermann*– Bielefeld University – Germany 3. *Tetsuya Ogata *– Waseda University – Japan 4. *Erhan Oztop *– Ozyegin Universiy – Turkey 5. * Stefan Wermter *– University of Hamburg – Germany *III. Submission * 1. For paper submission, use the following EasyChair web link: *Paper Submission <https://easychair.org/conferences/?conf=rlhrc2017>*. 2. Use the ACM SIGCHI format: *ACM SIGCHI Templates <http://www.sigchi.org/publications/chipubform>*. 3. Submitted papers should be limited to 2-4 pages maximum. The primary list of topics covers the following points (but not limited to): - Computational model for high-level cognitive capabilities - Predictive learning from sensorimotor information - Multimodal interaction and concept formulation - Human-robot communication and collaboration based on machine learning - Learning supported by external trainers by demonstration and imitation - Bayesian modeling - Learning with hierarchical and deep architectures - Interactive reinforcement learning * IV. Important Dates * 1. Paper submission: *15-September-2017* 2. Notification of acceptance: *25-September-2017* 3. Camera-ready version: *5-**October-2017* 4. Workshop: *17-October-2017* *V. Organizers * 1. *Takato Horii *– Osaka University – Japan 2. *Amir Aly *– Ritsumeikan University – Japan 3. *Yukie Nagai *– National Institute of Information and Communications Technology – Japan 4. * Takayuki Nagai *– The University of Electro-Communications – Japan -- *Amir Aly, Ph.D.* Senior Researcher Emergent Systems Laboratory College of Information Science and Engineering Ritsumeikan University 1-1-1 Noji Higashi, Kusatsu, Shiga 525-8577 Japan

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Postdoc position in electrophysiology/neural coding at Columbia University
by Qi Wang Aug. 28, 2017

Aug. 28, 2017

A postdoc position is available in the Laboratory for Neural Engineering and Control in the Department of Biomedical Engineering at Columbia University (http://neclab.bme.columbia.edu/) The project investigates the role of the locus coeruleus – norepinephrine (LC-NE) system in modulating neural coding, perception, and learning. The successful applicant should have a background in in-vivo single-unit recording and quantitative analytical methods. Experiences in behavioral training of rodents is a plus. We are looking for highly motivated researchers with a strong technical background, ideally with a PhD or equivalent in Biomedical Engineering, Neuroscience, Psychology, or a related discipline. Applicants should demonstrate excellent oral and written communication skills, and the ability to work effectively independently and as part of a multidisciplinary team. Start date is flexible. Salary will be commensurate to the candidate qualifications. Applicants should submit a CV, a brief description of research interests, and a list of three references. All application materials as well as any inquiries should be sent to qi.wang(a)columbia.edu.

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Bernstein 2017 Workshop: "Multiscale modeling and simulation"
by Salvador Dura Aug. 27, 2017

Aug. 27, 2017

Dear All, We would like to bring your attention to the* "Multiscale modeling and simulation" workshop* at the *Bernstein Conference 2017, Sept 12-13, Göttingen, Germany.* *Website: *http://www.nncn.de/en/bernstein-conference/2017/ satellite-workshops/multiscale-modeling-and-simulation-dura-bernal-lytton *Short abstract:* Understanding brain function requires characterizing the *interactions occurring across many temporal and spatial scales*. Mechanistic multiscale modeling aims to organize and explore these interactions across these scales. Multiscale models can provide insights into how changes at the molecular and cellular levels affect dynamics at local networks and brain areas. At the highest levels, they allow us to connect neural activity to theories of behavior, memory and cognition. The recent introduction of large neuroscience projects in US and EU Brain Research through Advancing Innovative Neurotechnologies (BRAIN) and Human Brain Project (HBP) respectively provide an opportunity to rapidly gather new and more accurate data to incorporate into the multiscale models. This workshop will present some of the* latest multiscale modeling tools and approaches in neuroscience, as well as representative examples of datadriven multiscale neural simulations*. The workshop aims to encourage both computational and experimental neuroscientists to make use of multiscale modeling in their research. *Organizers: *Salvador Dura-Bernal and Bill Lytton (SUNY Downstate) *Speakers:* *Tue, Sept 12:* - Bill Lytton (SUNY Downstate) - Jean Pierre Changeux (Pasteur Institute) - Volker Steuber (University of Hertfordshire) - Robert McDougal (Yale University) - Salvador Dura-Bernal (SUNY Downstate) - Cliff C Kerr (University of Sydney) *Wed, Sept 13:* - Szabolcs Kali (Hungarian Academy of Science/HBP) - Marianne Bezaire (Boston University) - Daniel Durstewitz (ZI Mannheim) - Kael Dali (Allen Institute for Brain Science) We look forward to seeing you there! Best Salva -- Salvador Durá-Bernal, Ph.D. Research Assistant Professor State University of New York Downstate Medical Center

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PhD, Master and Postdoc positions in theoretical neuroscience at the MPI for Brain Research
by Tatjana Tchumatchenko Aug. 27, 2017

Aug. 27, 2017

PhD, Master and Postdoc positions in theoretical neuroscience at the Max Planck Institute for Brain Research We are looking for undergraduate students interested in writing a Master or PhD thesis and also have open positions for Postdocs to join our group "Theory of neural dynamics" at the Max Planck Institute for Brain Research lead by Dr. Tatjana Tchumatchenko. Our group studies how networks of neurons encode and decode sensory stimuli and how these functions are related to computations that underlie cognitive functions and behavior. We develop models to address linear and non-linear properties of neuronal networks and have ongoing collaborations with experimental labs where we analyze in vitro as well as in vivo data and develop appropriate models to explain the observed phenomena. Successful applicants should have a strong background in a quantitative field such as physics, mathematics or computer science and should be interested in an interdisciplinary exchange with other disciplines such as biology or medicine. Life science majors interested in quantitative modeling work are also encouraged to apply, particularly if they would like to combine experiments and theory in their Master or Ph.D. thesis work. We are looking for candidates with strong English skills and prior programming experience. In order to make teamwork in our group enjoyable and fun, the ideal candidate should have a strong work ethic and have demonstrated consistent self-motivation skills. Female students are particularly encouraged to apply. Prospective students should apply by sending an email to theoryneuraldynamics(a)gmail.com which includes * a letter of motivation, * CV, * and a copy of the current academic transcripts To make your motivation letter easier to write for you and more informative for us, please check the list of questions to be answered in your motivation letter at http://www.tchumatchenko.de/Opportunities.html Looking forward to your applications! Tatjana Tchumatchenko

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Postdoctoral opportunity
by Timothy O'Leary Aug. 25, 2017

Aug. 25, 2017

Post-doctoral position in theoretical neuroscience, University of Cambridge Description We are seeking a highly creative and motivated Postdoctoral Research Assistant/Associate in Theoretical and Computational Neuroscience to join the research group of Dr Timothy O’Leary in the Department of Engineering, University of Cambridge (http://www.olearylab.org/) The successful applicant will undertake exciting collaborative research projects in systems neuroscience, with the opportunity to work closely with experimental laboratories in Harvard Medical School, HHMI Janelia and the Weizmann Institute of Science. The post will therefore involve significant travel. A range of projects is available, covering themes of neural representations of behaviour, neuromodulation and regulatory control in the nervous system. The successful applicant will have, or be near to obtaining, a PhD in theoretical neuroscience, applied mathematics, control engineering, physics, or theoretical biology, and will have extensive research experience demonstrated by a strong publication record. A solid grounding in neuroscience is important. The position is initially for three years with possibility of extension, with a 6 month probation period. The appointment commences December 1, 2017but start date is flexible within reason. We offer a competitive salary in line with experience and we especially encourage applications from minorities and underrepresented groups. Full application details are available here: http://www.jobs.cam.ac.uk/job/14796/ Closing date: 2017-10-02 Employment start date: 2017-12-01 Contract length: 3 years Institution: University of Cambridge *Timothy O'Leary* Department of Engineering, University of Cambridge, United Kingdom Phone +441223746527 Email tso24(a)cam.ac.uk

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advertised postdoc position
by Matthew Chalk Aug. 25, 2017

Aug. 25, 2017

Postdoc position in theoretical neuroscience, at the Vision Institute in Paris, France: Description: A postdoctoral position is available for a project with Matthew Chalk, at the Vision Institute (www.institut-vision.org/en/) within the University of Pierre and Marie Curie, in Paris, France. The project will involve investigating principles of neural coding in the retina. Specifically, the project will investigate how different coding objectives, such as optimising efficiency or encoding predictive information, can explain the diverse ways that neurons in the retina respond to visual stimulation. The postdoc will include both a theoretical and an experimental component. The theoretical part of the project will extend previous work by Chalk et al. to develop a general theory of optimal neural coding (Chalk et al. NIPS 2016, Chalk et al. bioArxiv 2016). The experimental part will involve running experiments to test this theory in the retina. The experimental part will be in close collaboration with members from the lab of Olivier Marre, who have developed techniques for recording from hundreds of retinal ganglion cells simultaneously (e.g. Marre et al. PLoS Comp. 2015). The Vision Institute is a stimulating environment for brain research. It brings together in a single building researchers, clinicians and industrial partners in order to discover, test and develop treatments and technological innovations for the benefit of visually impaired patients. The ideal candidate should have a PhD with a strong, quantitative background (ideally in fields such as machine learning and/or theoretical neuroscience). The position is funded for three years. Applications should include a CV, a statement of research interests (max 1 page), and two letters of recommendation. The earliest starting date will be 14/01/18. Electronic submissions in pdf-format are preferred and should be sent to Matthew Chalk (matthewjchalk(a)gmail.com <mailto:matthewjchalk@gmail.com>). Feel free to ask any informal questions about the position if you are interested.

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Fully funded PhD position on machine learning for neuroimaging data analysis
by Diego Sona Aug. 23, 2017

Aug. 23, 2017

We are seeking candidates for a PhD position entitled “Computational Methods for Brain Connectivity Analysis”. The research will aim at developing novel approaches based on machine learning for the analysis of structural and functional brain connectivity from neuroimaging data (e.g., fMRI, rsMRI, DTI, MEG, EEG, etc.). The aim is to better understand the brain and characterize the neurological and neurodegenerative diseases. The successful candidate will have the opportunity to work in an interdisciplinary environment. The applicant should have a background in machine learning and pattern recognition methodologies with a keen interest in neuroscience. The PhD grant is jointly supported by Fondazione Bruno Kessler (FBK) and Istituto Italiano di Tecnologia (IIT). The research activity will take place at the Neuroinformatics Laboratory (NILab, https://nilab.fbk.eu/ <https://nilab.fbk.eu/>) and the Pattern Analysis and Computer Vision Laboratory (PAVIS, http://pavis.iit.it/ <http://pavis.iit.it/>). NILab is an interdisciplinary laboratory raised as joint initiative between the Centre for Information Technology of FBK and the Centre for Mind/Brain Sciences of University of Trento (CIMeC, http://www.cimec.unitn.it <http://www.cimec.unitn.it/>). Interested candidates must apply for the PhD grant following the instructions in the call published by Università degli studi di Trento (see the application webpage http://ict.unitn.it/application/ict_doctoral_school <http://ict.unitn.it/application/ict_doctoral_school>) referring to position A5. Deadline for the formal application is August 31, 2017, hrs. 04.00 PM (Italian time, GMT +2) Interested candidates are also invited to contact Paolo Avesani (avesani(a)fbk.eu <mailto:avesani@fbk.eu>) and Diego Sona (diego.sona(a)iit.it <mailto:diego.sona@iit.it>) by emailing their CV and a short statement of interest in this position. For further information on the position and the application process refers to the following links http://ict.unitn.it <http://ict.unitn.it/> http://ict.unitn.it/application/project_specific_grants <http://ict.unitn.it/application/project_specific_grants> Diego Sona --------------------------------------------------------- Pattern Analysis & Computer Vision (PAVIS) Istituto Italiano di Tecnologia (IIT) Via Morego 30, 16163, Genova, Italy Phone: +39 010 71781 819 E-mail: diego.sona(a)iit.it pavis.iit.it/people/diego-sona ---------------------------------------------------------

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Assistant Professor Neural Mechanisms of Cognition and Behavior, Emory University (Atlanta, USA)
by Liu, Robert C Aug. 23, 2017

Aug. 23, 2017

Assistant Professor, Neural Mechanisms of Cognition and Behavior The Department of Psychology at Emory University invites applications for a tenure-track position at the level of assistant professor with an anticipated start date of August 1, 2018. We seek applicants to establish an independent, federally-funded program of research aimed at understanding mechanisms of cognition and behavior at biological and psychological levels with a goal of building on Emory's strengths in behavioral, cognitive, affective, social, computational, developmental, and/or comparative neuroscience. We also seek applicants with a strong commitment to undergraduate and graduate teaching. Laboratory space for small animals as well as research facilities for humans (including a research-dedicated 3T MRI scanner) are available. Applicants whose research uses cutting-edge techniques in small animals and bridges to studies with humans are particularly encouraged to apply. Ph.D. required. Candidates should submit applications at psychology.emory.edu. Please include a CV, a research statement, a teaching statement, two or three representative publications, and three letters of recommendation. Please also include a brief statement in your cover letter that addresses past activities and future plans to advance equity, inclusion, and diversity in your professional career. Review of applications will begin on November 1, 2017, and applications received up to 30 days after review begins will be given full consideration. Emory University (Atlanta, GA) is a diverse community that values multiple perspectives and is an Equal Opportunity/Affirmative Action/Disability/Veteran employer. Women, minorities, persons with disabilities and veterans are encouraged to apply. Robert C. Liu, PhD Associate Professor Department of Biology Emory University O. W. Rollins Research Center Rm 2131 1510 Clifton Rd NE Atlanta, GA 30322 USA Phone: +1 404-727-5274 Email: robert.liu(a)emory.edu<mailto:robert.liu@emory.edu> Lab Website<http://www.biology.emory.edu/research/Liu/html/index.php> ________________________________ This e-mail message (including any attachments) is for the sole use of the intended recipient(s) and may contain confidential and privileged information. If the reader of this message is not the intended recipient, you are hereby notified that any dissemination, distribution or copying of this message (including any attachments) is strictly prohibited. If you have received this message in error, please contact the sender by reply e-mail message and destroy all copies of the original message (including attachments).

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Doctoral student position - Robot-assisted modeling of spatial navigation paradigms in biological organisms
by samarasinghe＠ini.rub.de Aug. 23, 2017

Aug. 23, 2017

*Research **Position **at the Institute for Neural Compu**ta**ti**o**n * A position as *d**octoral student **in integrative **n**euroscience and **c**ognitive **s**cience *is available immediately in the group of Prof. Sen Cheng in the Institute for Neural Computation at the Ruhr University Bochum, Germany. The research will focus on robot-assisted modeling of spatial navigation paradigms in biological organisms. Robotic simulations, as well as, physical robots will be used to develop and evaluate the desired models. The position will be funded at 50% of the standard salary scale TV-L E13. It is initially limited to 1 year with the possibility of extension, depending on the availability of funding. Candidates should have an excellent degree in neuroscience, physics, mathematics, engineering, or a related field. Competence in mathematical modeling, and excellent programming skills (Python, C/C++, or Matlab) are mandatory. Candidates are further required to have a strong background in at least one of the following fields: robotics, computational neuroscience, or cognitive modeling. Experience with interdisciplinary research in integrative neuroscience and cognitive science and with collaborative research would be a further asset. The working language at the institute is English. To apply, please send a statement of your research interests, academic transcripts, and a complete CV in one PDF file to samarasinghe(a)ini.rub.de <mailto:samarasinghe@ini.rub.de> by 31.08.2017. Please also request from at least two academic referees that they send letters of reference directly to the same email address. Further information may be available at https://www.ini.rub.de/the_institute/jobs/. The Ruhr University Bochum provides a dynamic research environment in neuroscience and cognitive science. The Institute for Neural Computation unifies various core competencies extending from experimental and theoretical neuroscience to machine learning and robotics. The Ruhr University Bochum is committed to equal opportunity. We strongly encourage applications from qualified women and persons with disabilities. -- Vinita Samarasinghe M.Sc., M.A. Science Manager Arbeitsgruppe Computational Neuroscience Institut für Neuroinformatik Ruhr-Universität Bochum, NB 3/26 Universitätstr. 150 D-44780 Bochum Tel: +49 (0)234 32 27316 Email: samarasinghe(a)ini.rub.de Hours: Monday 9-12 & 14-16; Friday 9-12 & 14-16; Wednesday 12 - 16

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Memory GATE opens early for 2 theoretical PhD students at SISSA
by Alessandro Treves Aug. 23, 2017

Aug. 23, 2017

Memory research: Ground-breaking, Applied, and Technological Exchanges is an EU-funded Innovative Training Network coordinated by Francesco Battaglia and including groups at the Radboud (Nijmegen), UCLondon, NTNU-Trondheim, INSERM & AMU (Marseille), Weizmann, Janssen Pharma and SISSA, which will host 15 PhD students on projects taking different approaches to hippocampal memory functions, starting in early 2018. The two theorists to be hosted at SISSA, however, have to be admitted to its Cognitive Neuroscience PhD, by attending the exam in Trieste on Sept 11-12, 2017, see http://www.sissa.it ----------- Deadline August 31st, 2017 --------------- Ideal candidates, who can be of any nationality but must not have spent much time in Italy in the last 3 years, enjoy analytical, mathematical and computational excursions when seeking fundamental network understanding. Those admitted will be awarded a SISSA fellowship for the first few months, and later a much higher, EU-set M-GATE fellowship once the ITN operates. Feel free to inquire about limbo (then please send a CV) to ale(a)sissa.it -- Alessandro Treves http://people.sissa.it/~ale/limbo.html SISSA - Cognitive Neuroscience, via Bonomea 265, 34136 Trieste, Italy +39-040-3787623 Ambassador (BlaBlaCar) +39-349-2504602

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Neuromodulation of Neural Microcircuits NM2 Conference 2017
by Srikanth Ramaswamy Aug. 22, 2017

Aug. 22, 2017

We are delighted to announce the upcoming Neuromodulation of Neural Microcircuits (<https://nm2.epfl.ch/>NM2) Conference 2017<https://nm2.epfl.ch> (https://nm2.epfl.ch/) The NM2 Conference will be held at the EPFL, Lausanne, Switzerland on the 18th and 19th of Sep. 2017 and at the Campus Biotech in Geneva, Switzerland on the 20th of Sep. 2017. Neuromodulators dynamically reconfigure neural microcircuits and shape brain states by controlling the function of neurons and glia, dendrites, and synapses. NM2 will bring together world-leading experts to: • Identify the state-of-the-art mechanisms of the neuromodulation of neural microcircuits • Illuminate various strategies enabling the measurement of neuromodulatory states in brain health and disease • Integrate knowledge to build a unifying view of the neuromodulation of different brain regions • Inform and attract new talent to drive forward neuromodulation research • Inspire future directions that will transform our understanding of the neuromodulation of brain function and dysfunction and therapeutic intervention NM2 has an exciting program<https://nm2.epfl.ch/page-145616-en.html> with a stimulating lineup of speakers<https://nm2.epfl.ch/page-145624-en.html>! Please mark your calendars to participate in shaping the future course of neuromodulatory research! Registration<https://nm2.epfl.ch/page-145625-en.html> includes coffee breaks, lunch, refreshments and poster sessions. PhD. students and postdocs are particularly encouraged to submit poster abstracts<https://nm2.epfl.ch/page-146294-en.html>. Some abstracts will be selected for flash talks. Early bird registration is open until August 21st, 2017. We look forward to welcoming you at NM2 in beautiful Switzerland! Best regards from the scientific committee of NM2, Srikanth Ramaswamy Henry Markram Mriganka Sur Anita Disney Menahem Segal Michael Hasselmo Seung-Hee Lee Alexander Thiele Amy Arnsten

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Postdoctoral Fellowship: Enhancing Real-World Memory
by Christopher Honey Aug. 22, 2017

Aug. 22, 2017

POSTDOCTORAL FELLOW: ENHANCING REAL-WORLD MEMORY A fully-funded postdoctoral position is available in Dr. Christopher Honey's lab in the Department of Psychological and Brain Sciences at Johns Hopkins University (www.honeylab.org) Working with the Barense Lab at the University of Toronto, our team is developing a memory prosthetic device which enhances memory for everyday events. This postdoctoral research would lead investigations into how memory can be optimized by grouping, timing and framing of replay events. The ideal candidate would be conversant in both neuropsychological theory of memory as well as the computational analysis of real-world audiovisual data. Johns Hopkins is home to a large and vibrant community of neuroscience researchers, and features strong connections between psychology, systems and cognitive neuroscience, biomedical engineering and computer science. Postdoctoral fellows will have access to the MARCC computing cluster; a top-notch neuroimaging center, including 3T and 7T scanners; new TMS and EEG facilities are housed in the PBS department; human intracranial experiments are possible via neurology collaborators in Baltimore and Toronto. The targeted start date for this position is October 2017. The initial appointment is for one year, with the opportunity for renewal thereafter. The University is an Affirmative Action/Equal Opportunity Employer of women, minorities, protected veterans and individuals with disabilities and encourages applications from these and other protected group members. Consistent with the University's goals of achieving excellence in all areas, we will assess the comprehensive qualifications of each applicant. QUALIFICATIONS Candidates should have a PhD in a relevant field (e.g., psychology, cognitive science, neuroscience, physics, mathematics, computer science) and a record of published work related to memory and/or wearable devices. Strong programming skills are required. APPLICATION INSTRUCTIONS To apply, please email chris.honey(a)jhu.edu, providing: a current CV, a brief summary of research accomplishments and plans; two example publications or computational projects; contact information for three references.

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Postdoctoral researcher, neuroimaging & computational neuroscience
by Megan Peters Aug. 21, 2017

Aug. 21, 2017

Postdoctoral researcher, neuroimaging & computational neuroscience (Megan Peters) The Neural Computation Lab in the Department of Bioengineering at the University of California, Riverside, led by Dr. Megan Peters, is seeking a postdoctoral researcher. Topics of investigation include neural substrates of uncertainty, decision-making, and perceptual awareness using computational analysis and neuroimaging (fMRI, EEG). The successful candidate holds a Ph.D. or equivalent in computational neuroscience, bioengineering, applied math, computer science, or related field, and has substantial computational background in analyzing neuroimaging data (e.g., MVPA, connectivity, graph theory) and ideally computational modeling (Bayesian, signal detection theory, neural networks). Proficiency in at least one programming language (Matlab, Python, etc) is required. Our research group is part of a strong and lively neuroscience research community at UCR, and has strong ties to other groups in southern California and worldwide, including at UCLA (Hakwan Lau’s group; Michele Basso’s group; Alicia Izquierdo’s group), Advanced Telecommunications Research (ATR) in Kyoto (Mitsuo Kawato’s group), and Nagoya University (Kazuhisa Shibata’s group). Initial appointment will be for one year, with the possibility to renew up to five years. Compensation will be according to the NIH payscale. The University of California is an equal opportunity employer. Applications from women and underrepresented minorities are encouraged. To apply, please send a CV, statement of interests, up to 3 letters of recommendation and any relevant reprints to Dr. Peters at mpeters(a)engr.ucr.edu. We are accepting applications until the position is filled. -- Megan Peters, Ph.D. Assistant Professor Department of Bioengineering University of California, Riverside http://www.engr.ucr.edu/faculty/meganpeters.html

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postdoc in Barcelona to do single cell recordings in humans
by Quian Quiroga, Rodrigo (Prof.) Aug. 21, 2017

Aug. 21, 2017

*** Apologies for multiple postings*** Dear all, Please see below details of a postdoc position at the Barcelona ßeta Brain Research Center to study memory mechanisms by performing single cell recordings in humans in collaboration with Hospital del Mar. Cheers, Rodrigo Postdoc Position Barcelona ßeta Brain Research Center (BBRC) The Barcelona ßeta Brain Research Center (BBRC) offers a fully funded postdoc position at the research group headed by Professor Rodrigo Quian Quiroga. The group is part of a new Research Program on Memory, complementary to ongoing research at BBRC dealing with the Prevention of Alzheimer Disease. The group is associated to the epilepsy group headed by Dr. Gerardo Conesa at Hospital del Mar, a health center close to BBRC. Research will involve the study single cell recordings in humans. These recordings are performed in epileptic patients for curative surgery. In particular, the project will investigate concept cells (a.k.a. Jennifer Aniston neurons) – that means, neurons in the hippocampus and surrounding areas that selectively fire to specific concepts, like different pictures and the written or spoken name of a particular person (e.g. Quian Quiroga et al, Nature 2005; Quian Quiroga Nature Reviews Neuroscience 2012), which are involved in declarative memory functions. The successful candidate will contribute to performing recordings with patients at the Hospital del Mar and the analysis of the data to investigate the role of these neurons in memory formation, consolidation, long-term coding and recall. Candidates should have excellent quantitative skills (data processing, and programming, preferably in Matlab) and ideally, a strong background in neuroscience and experience with neurophysiology recordings. They should be able to work both independently and as part of a research team within the BBRC. The position is initially offered for 2 years, with the possibility to extend it for another 2 years. Salary will be competitive, depending on experience. The closing date for the applications is Monday 25th August 2017. Start date will be in October 2017. For application details and further particulars see: https://fpmaragall.org/en/wp-content/uploads/sites/3/2014/07/Postdoc_Neural… Informal inquiries are welcome and should be submitted electronically to: rh(a)fpmaragall.org Rodrigo Quian Quiroga Centre for Systems Neuroscience University of Leicester www.le.ac.uk/csn

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FW: 5th Baltic-Nordic School on Neuroinformatics BNNI 2017
by Marja-Leena Linne Aug. 20, 2017

Aug. 20, 2017

5th Baltic-Nordic School on Neuroinformatics BNNI 2017 Theoretical modelling of brain functions in neurological and psychiatric disorders: Advancing future neuroscience and medicine through Neuroinformatics methods Place: Neuroscience Institute Lithuanian University of Health Sciences Eiveniu str.4, Kaunas Lithuania Time: 6-7 October 2017 More information and applications at: http://web.lsmuni.lt/bnni/en Important dates: 3 September 2017: Application deadline 10 September 2017: Acceptance notification 6-7 October 2017: School We invite advanced master students, doctoral students, and postdoctoral researchers to participate in the BNNI 2017 to be held at the Neuroscience Institute, Lithuanian University of Health Sciences, Kaunas, Lithuania. The course is interdisciplinary and covers modeling at different levels of organization of the brain, focusing on neurological and psychiatric disorders. The course combines lectures, tutorials and computer exercises. This school is the fifth in the series of the Baltic-Nordic Courses on Neuroinformatics (BNNI 2013 in Kaunas, Lithuania; BNNI 2014 in Tampere, Finland; BNNI 2015 in Tartu, Estonia; BNNI in Warsaw 2016, Poland). The target audience of the course will be advanced master students, doctoral students and postdoctoral researchers in biomedical and technology sciences, from medicine, biology, psychology, to mathematics, informatics, information technology, physics, chemistry, who would like to get an introduction to neuroinformatics and computational neuroscience. Some experience with programming and quantitative reasoning as well as strong interest in computational and mathematical modeling of the brain will be desirable but not necessary to benefit from the school. Last year we had participants from 14 countries all over the world! Faculty includes Marja-Leena Linne, Tampere University of Technology, Finland Bruce Graham, University of Stirling, UK Daniel Wojcik, Nencki Institute of Experimental Biology, Warsaw, Poland Arnd Roth, University College London, UK Peter Jedlicka, NeuroScience Center, Goethe-University, Frankfurt, Germany Tuomo Mäki-Marttunen, Simula Research Laboratory, Oslo, Norway Rima Naginiene, Neuroscience Institute, Lithuanian University of Health Sciences, Kaunas, Lithuania Andrius Radziunas, Department of Neurosurgery, Medical Academy, and Neuroscience Institute, Lithuanian University of Health Sciences, Kaunas, Lithuania Ausra Saudargiene, Neuroscience Institute, Lithuanian University of Health Sciences, and Vytautas Magnus University, Kaunas, Lithuania and others. Venue The lectures will be held at the Neuroscience Institute, Lithuanian University of Health Sciences, Eivenių str. 4, Kaunas, Lithuania Practical arrangements There is a small tuition fee of 50 euros. The organizers will provide teaching materials, meals and coffee during the course. The participants are expected to cover their travel and health insurance expenses as well as lodging. The course is supported by the Research Council of Lithuania and Lithuanian University of Health Sciences. We are looking forward to welcoming you at the BNNI 2017 in Kaunas, Lithuania!

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Late registration open for Integrated Systems Neuroscience
by Mark Humphries Aug. 17, 2017

Aug. 17, 2017

Dear colleagues, late registration for the Integrated Systems Neuroscience meeting is now open until Friday September 1st Please register here: https://www.bmh.manchester.ac.uk/conferences-meetings/isn2017/ ISN is a forum for the state-of-the-art in systems and computational approaches to key neural circuits. This year our speakers range across population coding; decision-making; hippocampus; whole CNS imaging; cortical dynamics; and motor circuits Our Speakers Rune Berg (Copenhagen University) Tiago Branco (Sainsbury Wellcome Centre for Neural Circuits) Neil Burgess (Institute of Cognitive Neuroscience, UCL) Megan Carey (Champalimaud Institute, Lisbon) Claudia Clopath (Imperial College, London) Kate Jeffery (UCL) Christian Machens (Champalimaud Institute, Lisbon) Jonathan Pillow (Princeton) Simon Peron (New York University) Manuel Zimmer (IMP, Austria) ISN2017 is being held in Manchester, UK, on the 7-8th September. Any questions? Late-breaking poster? Please contact us at isn2017(a)manchester.ac.uk<mailto:isn2017@manchester.ac.uk> Hope to see you in Manchester! Mark Humphries & Rasmus Petersen Dr Mark Humphries | MRC Senior non-Clinical Research Fellow | Faculty of Biology, Medicine & Health | University of Manchester @markdhumphries Public blog: medium.com/the-spike<http://medium.com/the-spike>

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Open position: Expert in machine learning and high-performance computing
by Daniel Zysman Aug. 16, 2017

Aug. 16, 2017

The Department of Brain and Cognitive Sciences seeks an expert in machine learning and high-performance computing to collaborate on cutting edge research on neuroscience, perception, cognition, and artificial intelligence. The department is a world leader in computational approaches to brain science, and is home to state-of-the-art computing resources as well as the Center for Brains, Minds and Machines, a multi-institutional NSF Science and Technology Center dedicated to the study of intelligence. Salary will be competitive with industry. To apply: https://careers.peopleclick.com/careerscp/client_mit/external/jobDetails.do… <https://careers.peopleclick.com/careerscp/client_mit/external/jobDetails.do…> For more information about our department: https://bcs.mit.edu/ <https://bcs.mit.edu/> Job Description: PROGRAMMER/SOFTWARE DEVELOPMENT ENGINEER/COMPUTATIONAL AND MACHINE LEARNING SPECIALIST, Brain and Cognitive Sciences, to help tackle challenging problems in high-performance computing methods and systems, machine learning, management of large datasets, and artificial intelligence. Responsibilities include helping researchers translate computational algorithms into efficiently functioning (especially parallelized and GPU optimized) code; assisting with installation and implementation of third-party tools; staying up-to-date with cutting-edge computational techniques; providing guidance for storage and management of large data sets; developing and maintaining online courses for computing resources, running in-person tutorials on specific software packages/tools, and helping transition users to new computing tools; providing educational support and training to users of the departmental computing cluster; and monitoring cluster usage and resolving problems. Job Requirements: Bachelor’s degree (advanced degree preferred) in a scientific field or computer science; at least four years’ experience in scientific high-performance (cluster) computing; familiarity with Slurm and Lustre; broad computational background with knowledge of Unix, HPC algorithms, GPU computing, programming models, debuggers, and performance tools; software development experience, especially Python and MATLAB, but also R, Lua, JavaScript, etc.; knowledge of high-level APIs for HPC computing; expertise installing and maintaining third-party software in an HPC environment and with container technology, especially in the context of computational reproducibility; familiarity with mathematical algorithms for high-performance computing, use or design of HPC profiling or optimization tools, and deep neural networks; ability to work effectively with scientists and engineers; initiative, tact, and judgment in developing solutions for users; excellent interpersonal skills and ability to communicate effectively, orally, in writing, and via live presentations; demonstrated ability to assume leadership roles, grasp complex problems, and develop solutions; and extensive background in high-performance computing. MIT is an equal employment opportunity employer. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, color, sex, sexual orientation, gender identity, religion, disability, age, genetic information, veteran status, ancestry, or national or ethnic origin. ------------------------------------------------------ Daniel Zysman Computational Course Co-Instructor MIT, Department of Brain & Cognitive Sciences

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Fully funded PhD studentship in Computational Neuroscience
by Vassilis Cutsuridis Aug. 16, 2017

Aug. 16, 2017

PhD Position in Computational Neuroscience (EU/UK candidates only) MLearn Research Group (http://mlearn.lincoln.ac.uk/) School of Computer Science University of Lincoln UK Applications are invited for a PhD position in the Machine Learning (MLearn) Research Group at the University of Lincoln. Projects involve the development and simulation of models of neuronal networks (microcircuits) of learning and memory in animal and human entorhinal cortex and hippocampus in health and disease (e.g. epilepsy, schizophrenia, Alzheimer's disease). A starting point of the project is the paper by Cutsuridis V, et al. (2010). Encoding and retrieval in the hippocampal CA1 microcircuit model. *Hippocampus*, 20(3): 423-446. <http://vassiliscutsuridis.com/docs/Journal_papers/CutCobGraHippo2010.pdf> <http://mlearn.lincoln.ac.uk> Student applicants should have excellent computational and numerical skills and a very good first degree in computer science, engineering, maths, physics, or a related discipline. Successful student candidates are eligible for a research studentship award from the University (GBP 14,553 per annum bursary plus payment of the student fees). This PhD studentship is ONLY OPEN to UK/EU students. The ideal candidate should be highly motivated, technically skilled, a team player and driven to push forward the development of the next generation of deep associative memory neural-networks. Your written and spoken English skills should be excellent. As a PhD student, you may also have the opportunity to teach as a demonstrator in the School of Computer Science. Research in Computer Science at the University of Lincoln has been recognised as internationally excellent and world leading. The School of Computer Science provides a very stimulating environment, offering a large number of specialised and interdisciplinary seminars as well as general training and researcher development opportunities. The University is situated in Lincoln, two hours northeast of London. Please contact Dr Vassilis Cutsuridis (vcutsuridis(a)lincoln.ac.uk) or Prof. Stefanos Kollias (skollias(a)lincoln.ac.uk) for informal enquiries. If you’re interested to apply, please email your CV, a brief statement of your scientific interests, and three reference letters to Dr. Vassilis Cutsuridis (vcutsuridis(a)lincoln.ac.uk) <vcutsuridis(a)lincoln.ac.uk> Applications will be assessed on a rolling basis. Vassilis Cutsuridis School of Computer Science University of Lincoln Lincoln LN6 7TS U.K. Tel: +44 (0) 1522 83 5107 Email: vcutsuridis(a)lincoln.ac.uk Web: http://staff.lincoln.ac.uk/vcutsuridis Personal Web: http://www.vassiliscutsuridis.com/

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Postdoctoral position / Optimizing NEST for Modular Supercomputing Architecture
by Hans Ekkehard Plesser Aug. 15, 2017

Aug. 15, 2017

com Dear Colleagues! I am looking for a post-doc to join my group to work on optimizing NEST (www.nest-simulator.org) for a novel modular supercomputing architecture developed by the DEEP-EST collaboration (www.deep-projects.eu) and to combine NEST simulations with simultaneous detailed LFP model (HybridLFPy, http://inm-6.github.io/hybridLFPy) or spike-train analysis (Elephant, neuralensemble.org/elephant) exploiting the heterogeneous DEEP-EST architecture. The position is funded by DEEP-EST, an EU FET-HPC project, coordinated by Forschungszentrum Jülich and involves academic and industry partners. The position is available immediately until the end of the project (June 2020). The full announcement for the position is available at https://www.jobbnorge.no/en/available-jobs/job/141149/postdoctoral-fellow-i… Please get in touch if you have any questions! Hans Ekkehard -- Dr. Hans Ekkehard Plesser Associate Professor Faculty of Science and Technology Norwegian University of Life Sciences PO Box 5003, 1432 Aas, Norway Phone +47 6723 1560 Email hans.ekkehard.plesser(a)nmbu.no Home http://arken.nmbu.no/~plesser

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Leaders and followers: Quantifying consistency in spatio-temporal propagation pattern
by Thomas Kreuz Aug. 15, 2017

Aug. 15, 2017

Dear all, may I kindly draw your attention to our paper on the new multivariate directional measure *SPIKE-Order*. In this paper we propose a new approach to quantify consistency of spatio-temporal propagation patterns in sequences of discrete events (e.g. spike trains). This includes a sorting from leader to follower. As usual we show some applications to neurophysiological data. *Leaders and followers: Quantifying consistency in spatio-temporal propagation pattern <http://iopscience.iop.org/article/10.1088/1367-2630/aa68c3/meta>* Thomas Kreuz, Eero Satuvuori, Martin Pofahl and Mario Mulansky New J. Phys., *19*, 043028 (2017). Abstract: Repetitive spatio-temporal propagation patterns are encountered in fields as wide-ranging as climatology, social communication and network science. In neuroscience, perfectly consistent repetitions of the same global propagation pattern are called a *synfire pattern*. For any recording of sequences of discrete events (in neuroscience terminology: sets of spike trains) the questions arise how closely it resembles such a synfire pattern and which are the spike trains that lead/follow. Here we address these questions and introduce an algorithm built on two new indicators, termed *SPIKE-order* and *spike train order*, that define the *synfire indicator* value, which allows to sort multiple spike trains from leader to follower and to quantify the consistency of the temporal leader-follower relationships for both the original and the optimized sorting. We demonstrate our new approach using artificially generated datasets before we apply it to analyze the consistency of propagation patterns in two real datasets from neuroscience (giant depolarized potentials in mice slices) and climatology (El Niño sea surface temperature recordings). The new algorithm is distinguished by conceptual and practical simplicity, low computational cost, as well as flexibility and universality. Implementations are provided online in three free code packages called SPIKY <http://www.fi.isc.cnr.it/users/thomas.kreuz/Source-Code/SPIKY.html> (Matlab GUI), PySpike <http://mariomulansky.github.io/PySpike/>(Python library) and, most recently, cSPIKE <http://www.fi.isc.cnr.it/users/thomas.kreuz/Source-Code/cSPIKE.html>(Matlab command line with MEX-files). Best regards, Thomas Kreuz PS: Three further recent articles: *Measures of spike train synchrony for data with multiple time scales <http://www.sciencedirect.com/science/article/pii/S0165027017301619>* Eero Satuvuori, Mario Mulansky, Nebojsa Bozanic, Irene Malvestio, Fleur Zeldenrust, Kerstin Lenk, Thomas Kreuz JNeurosci Methods *287*, 25 (2017). Background Measures of spike train synchrony are widely used in both experimental and computational neuroscience. Time-scale independent and parameter-free measures, such as the ISI-distance, the SPIKE-distance and SPIKE-synchronization, are preferable to time scale parametric measures, since by adapting to the local firing rate they take into account all the time scales of a given dataset. New method In data containing multiple time scales (e.g. regular spiking and bursts) one is typically less interested in the smallest time scales and a more adaptive approach is needed. Here we propose the A-ISI-distance, the A-SPIKE-distance and A-SPIKE-synchronization, which generalize the original measures by considering the local relative to the global time scales. For the A-SPIKE-distance we also introduce a rate-independent extension called the RIA-SPIKE-distance, which focuses specifically on spike timing. Results The adaptive generalizations A-ISI-distance and A-SPIKE-distance allow to disregard spike time differences that are not relevant on a more global scale. A-SPIKE-synchronization does not any longer demand an unreasonably high accuracy for spike doublets and coinciding bursts. Finally, the RIA-SPIKE-distance proves to be independent of rate ratios between spike trains. Comparison with existing methods We find that compared to the original versions the A-ISI-distance and the A-SPIKE-distance yield improvements for spike trains containing different time scales without exhibiting any unwanted side effects in other examples. A-SPIKE-synchronization matches spikes more efficiently than SPIKE-synchronization. Conclusions With these proposals we have completed the picture, since we now provide adaptive generalized measures that are sensitive to firing rate only (A-ISI-distance), to timing only (ARI-SPIKE-distance), and to both at the same time (A-SPIKE-distance). *Robustness and versatility of a nonlinear interdependence method for directional coupling detection from spike trains <https://journals.aps.org/pre/abstract/10.1103/PhysRevE.96.022203>* Irene Malvestio, Thomas Kreuz, Ralph G Andrzejak Physical Review E *96*, 022203 (2017). The detection of directional couplings between dynamics based on measured spike trains is a crucial problem in the understanding of many different systems. In particular, in neuroscience it is important to assess the connectivity between neurons. One of the approaches that can estimate directional coupling from the analysis of point processes is the nonlinear interdependence measure L. Although its efficacy has already been demonstrated, it still needs to be tested under more challenging and realistic conditions prior to an application to real data. Thus, in this paper we use the Hindmarsh-Rose model system to test the method in the presence of noise and for different spiking regimes. We also examine the influence of different parameters and spike train distances. Our results show that the measure L is versatile and robust to various types of noise, and thus suitable for application to experimental data. *SPIKE-order <http://www.scholarpedia.org/article/SPIKE-order>* Thomas Kreuz, Eero Satuvuori, Mario Mulansky Scholarpedia, *12*(7):42441 (2017). -- Institute for complex systems, CNR Via Madonna del Piano 10 50119 Sesto Fiorentino (Italy) Tel: +39-349-0748506 Email: thomas.kreuz(a)cnr.it Webpage: http://www.fi.isc.cnr.it/users/thomas.kreuz/

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