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CfP: Computationally Intelligent Methods in Processing and Analysis of Neuronal Big Data at BI 2018, Arlington, Texas, USA.
by Mufti Mahmud May 31, 2018

May 31, 2018

*[Apologies for cross posting.]* *Call for Paper for Special Session on * *Computationally Intelligent Methods in Processing and Analysis of Neuronal Big Data* *11th Brain Informatics Conference (BI 2018), Arlington, Texas, USA, December 7-9, 2018* *Web: http://uta.engineering/conferences/bi-2018/ <http://uta.engineering/conferences/bi-2018/>* Organizers: *Mufti Mahmud1, M Shamim Kaiser2, Ning Zhong3, Nitish V Thakor4* *1* *Computing and Technology, Nottingham Trent University, NG11 8NS – Nottingham, UK* 2*Institute of Information Technology, Jahangirnagar University, Savar, 1342 – Dhaka, Bangladesh* 3*Dept. of Life Science and Informatics, Maebashi Institute of Technology, 371-0816 - Maebashi-City, Japan* *4**Singapore Institute for Neurotechnology, National University of Singapore, 117456 – Singapore; & * *Dept. of Biomedical Engineering, Johns Hopkins University, Baltimore, 21205 – MD, USA* *Introduction:* The brain receives and processes information simultaneously coming from diverse sources. The neurons, being the basic information processing units, interconnect to each other to form hierarchical and/or parallel pathways. Technologies related to neural systems engineering have been employed to study these pathways along with processing and modelling of neuronal data for disease diagnosis and brain decoding purposes. Combining both experimental and computational approaches in recent years, thanks to the advancements in neurotechniques, scientists can access large amount of neuronal data and apply computationally intelligent and nature-inspired machine learning techniques including deep learning and reinforcement learning on those data to suggest next generation experimental design aiming to decipher brain’s information processing capabilities and diagnose its diseases. *Scope:* Developing data-intensive and intelligent tools, as well as sophisticated neurotechniques, to process and analyse the neuronal big data is one of the biggest challenges posed to today’s multidisciplinary brain science community. To share recent progress in decoding neuronal information processing, both in healthy and diseased brain, this special session aims to provide a forum for scientists from diverse disciplines including – computer, electrical, biomedical, and neuro engineering – who are looking for more relevant information in interpreting brain functions and diagnosing diseases using expert and computationally intelligent systems. This special session expects to attract papers on recent research progress in the area of intelligent computational tools and techniques in acquiring and processing neuronal big data. The focus areas include, but not limited to, the following: Ø Neural systems engineering and technology to study neural pathways; Ø Processing and modelling of neuronal data for disease diagnosis and brain decoding; Ø Bio-inspired methods for network analysis and pattern recognition in neural data; Ø Novel machine learning techniques for neuronal big data analysis; Ø Application of deep and reinforcement learning to neuronal big data analysis; Ø Computationally intelligent techniques for neuroscience applications; Ø Neuroinformatics (including cloud computing and real-time systems); Ø Cognitive science applications (learning, workload, decision making, etc.) and data analytics; Ø Computational and imaging methods for human brain connectome; and Ø Information analysis in human brain machine interface (invasive, noninvasive). *Submission of papers:* Submit Springer Lecture Notes in Computer Science (LNCS) complaint – 10 page – pdf paper to the Special Session following the steps below: Ø Prepare the paper as per the Springer LNCS template from: http://www.springer.com/us/computer-science/lncs/conference-proceedings-gui… Ø Visit https://wi-lab.com/cyberchair/2018/bi18/scripts/ws_submit.php?subarea=S Ø Select the link: Special session on Computationally Intelligent Methods in Processing and Analysis of Neuronal Big Data Ø Select the link Submit a New Paper (TYPE I Submission) Ø Provide paper details (i.e., Author(s), Paper Title, Abstract, Keywords, PDF file to upload). *Important dates:* Ø Paper submission deadline: *30 July 2018* Ø Decision notification: *30 August 2018* Ø Special Session date: *7 December 2018* Ø Conference dates: *8-9 December 2018*. -- *Mufti Mahmud, PhD* | (Senior) Lecturer of Computing & Technology <https://www.ntu.ac.uk/sat/about/academic_teams/comp_tech.html> | School of Science & Technology <https://www.ntu.ac.uk/sat/> Office: ERD200 | Nottingham Trent University <https://www.ntu.ac.uk/> | Clifton Campus | NG11 8NS – Nottingham, UK Phone: +44 (0)115 84 83202 | Email: mufti.mahmud(a)ntu.ac.uk Meeting requests: https://doodle.com/mufti http://orcid.org/0000-0002-2037-8348 https://sites.google.com/site/muftimahmud/ https://scholar.google.com/citations?user=L8em2YoAAAAJ&hl=en Senior Member, IEEE <https://www.ieee.org/> & ACM <https://www.acm.org/> Associate Editor, IEEE Access <http://ieeeaccess.ieee.org/> Editorial Board Member, Cognitive Computation <https://www.springer.com/biomed/neuroscience/journal/12559> & Big Data Analytics <https://bdataanalytics.biomedcentral.com/>

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New book: Neural Information Theory
by James V Stone May 31, 2018

May 31, 2018

I'd like to announce the publication of this book: Principles of Neural Information Theory: Computational Neuroscience and Metabolic Efficiency by James V Stone. Reviews, synopsis, and table of contents can be found here: http://sebtelpress.com regards, James V Stone, University of Sheffield, UK.

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[High Performance Computing] Become a specialist!
by Master in HPC May 31, 2018

May 31, 2018

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PhD studentship in Biocomputation Research Group, Centre for Computer Science and Informatics Research, University of Hertfordshire
by Shabnam Kadir May 30, 2018

May 30, 2018

Applications are invited for a *PhD studentship* on *Computational frameworks for high-dimensional neural data* with *Dr. Shabnam Kadir *in the *Biocomputation Research Group* in the Centre for Computer Science and Informatics Research, University of Hertfordshire, U.K. *Project Description* New developments in experimental technology have led to petabytes of raw data being produced by experimental neuroscientists, which are increasingly publicly available, e.g. Allen Institute data http://www.brain-map.org/. In particular, we are in the realm where population recordings of tens of thousands of neurons are feasible thanks to, e.g. a new generation of large dense probes for electrophysiological recordings, imaging using 2-photon microscopy coupled with calcium fluorescent sensors. Large scale neuronal recordings require novel approaches for both processing and quantitative analysis. As well as using techniques from high-dimensional statistics, machine learning, information theory, we aim to explore new approaches from mathematical fields outside statistics, such as algebraic topology. The study of networks is a particularly important topic in neuroscience: neurons communicate with each other electrically via synapses, forming intricate networks. These networks can be studied using techniques from computational topology (e.g. persistent homology, clique topology). These could be used to extract information about subnetworks and assemblies, both from large scale recordings, and via connectomics derived from simulations (Blue Brain Project). We aim in this project to go beyond spike sorting and develop new tools and computational frameworks which would help interpret high dimensional data and interrogate how information is being processed by the brain, e.g. How are sensory stimuli (location in environment, visual and auditory stimuli) encoded? How can we characterise the neural activity associated with memory, attention, decision making and motor control? We shall be collaborating with labs at Imperial, Pennsylvania State University and UCL. More information can be found here: http://www.herts.ac.uk/_ _data/assets/pdf_file/0003/187455/Dec2017-computational-fram eworks-for-high-dimensional-neural-data.pdf *Requirements * We are looking for candidates with the following profile: - Strong first degree in a quantitative field such as mathematics, physics, computer science, engineering, computational neuroscience. - Strong programming skills (e.g. Python, MATLAB, C++). - Interest in neuroscience and biology would be helpful. A studentship from the PhD Programme in Computer Science provides approximately £14,750 per annum bursary plus the payment of student fees. Applicants from outside the UK or EU are eligible. Research in Computer Science at the University of Hertfordshire has been recognised as excellent in the latest Research Excellence Framework Assessment (2014), with 50% of the research submitted rated as internationally excellent or world-leading. The Centre for Computer Science and Informatics Research 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 Hatfield, in the green belt just north of London. Please contact *Dr Shabnam Kadir* (s.kadir2(a)herts.ac.uk) for informal enquiries. Application forms are available under http://www.herts.ac.uk/a pply/schools-of-study/computer-science/our-research/the-phd- programme-in-computer-science and should be returned to Mrs Lorraine Nicholls and Mrs Emma Thorogood, Research Student Administrators, University of Hertfordshire, College Lane, Hatfield, Herts, AL10 9AB, Tel: 01707 286083, doctoralcollegeadmissions(a)herts.ac.uk. The short-listing process will begin on 25th June 2018. ------------------------------------------------------------ ---------------------------------------------------- Dr Shabnam Kadir Senior Lecturer School of Computer Science, University of Hertfordshire, Hatfield, Hertfordshire AL10 9AB, United Kingdom. Tel. +44 1707 284641 ------------------------------------------------------------ ----------------------------------------------------

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Faculty position in systems neuroscience, U of Montreal
by Paul Cisek May 30, 2018

May 30, 2018

Professor in Systems/Computational Neuroscience Faculty of medicine / Department of neurosciences Mandate description The Département de neurosciences at the Université de Montréal invites applications for a faculty position at the assistant or associate level, in Systems/Computational Neuroscience. We are seeking candidates who use experimental and/or computational approaches to study how large-scale distributed brain networks implement behavioural-level phenomena such as sensorimotor control and decision-making, with a particular emphasis on system-level learning mechanisms. Ideal candidates will either combine multi-electrode, multi-area neurophysiological studies in behaving animals (in particular non-human primates) with sophisticated computational modeling of brain function, or alternatively, will use predominantly computational approaches to study how biologically realistic large-scale and recurrent network models simulate behavioral-level phenomena. The Département de neurosciences offers state of the art laboratory space and animal facilities for rodent and non-human primates research. Montréal is a rich academic environment, with 4 major universities and a strong tradition of systems neuroscience. The candidates will have outstanding opportunities for collaborations with other systems neuroscientists at the Université de Montréal, McGill University, Concordia University and the Université du Québec à Montréal, as well as with leading experts in artificial intelligence, machine learning and deep-learning networks who are centered in the MILA/IVADO at the Université de Montréal. Responsibilities - The appointed candidate will be expected to maintain an active research program, supervise graduate students, have international collaborations, contribute to the academic life of the Department of Neurosciences, and teach undergraduate and graduate courses. - The candidate will collaborate closely with researchers working in three affiliated research centers at University of Montreal: CHU-Ste Justine (Pediatric Hospital), Centre Hospitalier Universitaire de Montréal, Hôpital du Sacré-Coeur de Montréal. - The teaching language is French; consequently, non-French-speaking candidates should become able to teach in French no longer than three years after their appointment. Requirements - The candidate needs to hold a PhD in neurosciences (or equivalent) and demonstrate significant experience at the post-doctoral level in the field of computational neurosciences. - The candidate needs to show exceptional track record in the field, including in sensorimotor control, decision making, neurophysiological studies in living animal, and computational approaches in order to study how neural network are modeling behavior. - The candidate needs to hold teaching experience at graduate and undergraduate levels, as well as experience in supervising post-doctoral fellowships, research assistants, and highly qualified research personal. - We will prioritize candidates with exceptional research productivity with a publication of articles in the best journals in the field, as well as a strong track record of research funding from national and international research agencies. - The ability and interest of the candidate to work in a multidisciplinary team (biochemists, biologists, engineers, bio informaticians, and clinicians) is mandatory. - Have sufficient knowledge of the French language (written and spoken) or be determined to learn it *. General information Posting No: MED 4-18 / 4 Posting period: June 15th, 2018 Salary: The University of Montreal offers a competitive salary and a complete range of employee benefits Start date: Autumn 2018. The announcement will remain open until the selection committee finds an acceptable candidacy. Application procedure Interested candidates should send their curriculum vitae, a letter explaining their motivation, research interest and competence in their area of expertise, and three letters of support, no later than June 15th 2018; at the following address (email correspondence is preferred): Dr Patrick Cossette, directeur Département de neurosciences Faculté de médecine Université de Montréal C.P. 6128, succursale Centre-ville Montréal (Québec) H3C 3J7 E-mail : nancy.crete(a)umontreal.ca <mailto:nancy.crete@umontreal.ca> *Linguistic Policy The Université de Montréal is a Québec University with an international reputation. French is the language of instruction. To renew its teaching faculty, the University is intensively recruiting the worlds best specialists. In accordance with the institutions language policy, the Université de Montréal provides support for newly-recruited faculty to attain proficiency in French. Confidentiality The Université de Montréal application process allows all regular professors in the Department to have access to all documents unless the applicant explicitly states in her or his cover letter that access to the application should be limited to the selection committee. This restriction on accessibility will be lifted if the applicant is invited for an interview. Equal Access Employment Program Université de Montréal promotes diversity in its workforce and encourages members of visible and ethnic minorities as well as women, Aboriginal people, persons with disabilities and people of all sexual orientations and gender identities to apply. Immigration Requirements We invite all qualified candidates to apply at Université de Montréal. However, in accordance with immigration requirements in Canada, please note that priority will be given to Canadian citizens and permanent residents. Paul Cisek, PhD Département de neurosciences Université de Montréal Physical: 2960 chemin de la tour, local 4117 Montréal, QC H3T 1J4 CANADA Mailing: CP 6128 Succursale centre-ville, Montréal, QC H3C 3J7 CANADA e-mail: <mailto:paul.cisek@gmail.com> paul.cisek(a)gmail.com Web: www.cisek.org/pavel <http://www.cisek.org/pavel>

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SenseLab survey
by Ted Carnevale May 29, 2018

May 29, 2018

The SenseLab project applies neuroinformatics methods to make it easier to discover, understand, and reuse neuroscience models, and to relate those models to experimental data. We invite you to help guide the future development of ModelDB http://modeldb.yale.edu and the other SenseLab databases by taking this short survey: https://yalesurvey.ca1.qualtrics.com/jfe/form/SV_2sZuf5bxk99nTnf (Yale recipients: the survey's original URL is https:// yalesurvey.ca1.qualtrics.com/jfe/form/SV_2sZuf5bxk99nTnf minus the space between // and yalesurvey) The SenseLab Team https://senselab.med.yale.edu/ModelDB/modeldb_credits.cshtml

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Multiple Openings for Research Scientists and Engineers to Reverse Engineer intelligence
by Lopez, Camila May 29, 2018

May 29, 2018

Hi, Can you please post this job ad? Multiple Openings for Research Scientists and Engineers to Reverse Engineer intelligence We are looking for exceptionally talented researchers that share our vision: to discover new computational principles of brain intelligence and apply these principles to create fundamentally new algorithms for machine intelligence. We are particularly interested in candidates with expertise in machine learning, computational neuroscience or with strong quantitative background in Mathematics, Statistics, Physics or Computer Science. Our NINAI (Neuro-Inspired Networks for Artificial Intelligence) research team is interdisciplinary and international, with expertise ranging from large-scale neurophysiology and brain circuit analysis to deep learning. POSITIONS: We have opportunities in several project components and multiple locations, and all participants will interact extensively across multiple scientific disciplines and multiple sites. Highest-priority topics include: * Developing new architectures for deep networks * Neuro-inspired networks for real-world tasks * Functional modeling of neuronal microcircuits * Probabilistic inference by population codes * Statistical analysis of large-scale neural data from behaving animals THE TEAM: The project is led by Andreas Tolias (PI) and Xaq Pitkow (co-PI), from Baylor College of Medicine, and includes researchers from Columbia, Cornell, Rice University, University of Toronto, University of Tübingen, the Allen Institute, and Princeton: Matthias Bethge, Liam Paninski, Ankit Patel, Clay Reid, Sebastian Seung, Raquel Urtasun, Chris Xu, Richard Zemel. For detailed information about the team and its members, please see our website, ninai.org<http://ninai.org/>. QUALIFICATIONS: Candidates must have a record of productivity, excellent quantitative skills, good communication skills, and creativity. Experience in Machine Learning and in particular Deep Learning is desired. APPLYING: The positions provide a competitive annual salary and benefits, and outstanding scientific opportunities. Applicants should email a CV, letter of research interests, and contact information for three references to info(a)ninai.org<mailto:info@ninai.org>, camilal(a)bcm.edu<mailto:camilal@bcm.edu> and astolias(a)bcm.edu<mailto:astolias@bcm.edu>. We look forward to hearing from you!

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IEEE Special issue deadline extended!
by Steve Mehrkanoon May 29, 2018

May 29, 2018

Paper Submission Deadline Extended! CALL FOR PAPERS Special issue: Neural Systems Engineering and Mathematical Modelling of Brain dynamics using ECoG/EEG/MEG oscillations and Machine learning methods Journal IEEE Transactions on Neural Systems and Rehabilitation Engineering New Submission Deadline: 01/07/2018 Submission portal: https://mc.manuscriptcentral.com/tnsre-embs Contributions will receive prompt and thorough peer review and will be published online ahead of print after acceptance. In humans, interactions between neuronal circuits, systems and signals among micro-, meso- and macro-scales of brain dynamics underpin the functional organisation of the brain that supports our daily life activity. How efficiently neuronal circuits such as cortico-cortical, cortico-thalamic and thalamo-cortical networks interact among these multiple spatial scales remains to be fully elucidated. Mathematical, computational and experimental neuroscientists apply a variety of methods, techniques and algorithms, both in animals and humans, ranging from single cell recordings to whole brain imaging, in order to identify the core mechanisms that govern the interactions among these scales. Although our knowledge of neural mechanisms, circuits and networks underlying brain dynamics and functions constantly grows, the integration of this knowledge to provide a conceptual framework of emergent behaviour and pattern formation occurring on different levels of spatial organisation remains challenging. Authors are invited to submit original or review articles addressing mechanisms of emergent brain dynamics inferred from the analysis of ECoG/EEG/MEG, on all levels of complexity. Specifically, articles integrating (i) computational neuroscience, and (ii) mathematical models of biologically realistic neuronal networks and machine learning methods are welcome. In this special issue, Guest Editor Dr Steve Mehrkanoon welcomes papers that address many of the challenges of mathematical and computational models of the brain networks and dynamics given the measurement data ECoG/EEG/MEG. The scope of this special issue is interdisciplinary. The list of possible topics includes, but is not limited to: * New developments in computational and mathematical models of mean field theory integrated with ECoG/EEG/MEG modalities. * Multi-modal and combinatorial fusion of ECoG/EEG/MEG data and brain connectivity machine learning. * Development of data-driven machine learning techniques to identify the mechanisms of emergent spatia-temporal dynamics within the framework of network topology. * Development of computational and mathematical models for bridging the scales of brain dynamics. * Cortical network modelling and formal conceptual models of cortical oscillations. * Application of deep learning and machine learning algorithms in functional, structural and effective network analysis and predictive models of brain dynamics. * New cutting-edge numerical analysis and techniques to simulate meso- and macro-scale brain dynamics. * Adaptive mathematical and computational models of network dynamics (e.g., brain development and aging studies). * Statistical methods for assessing individual and population brain connectivity data. Guest Editors 1. Dr Steve Mehrkanoon The University of Queensland Centre for Clinical Research, Faculty of Medicine, School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia Contact: s.mehrkanoon(a)uq.edu.au<mailto:s.mehrkanoon@uq.edu.au> 1. Professor David Liley Centre for Human Psychopharmacology, School of Health Sciences, Swinburne University of Technology, Melbourne, Australia Contact: dliley(a)swin.edu.au<mailto:dliley@swin.edu.au> 1. Dr Siamak Mehrkanoon Department of Electrical Engineering (ESAT), University of Leuven, KU Leuven, Belgium Contact: Siamak.Mehrkanoon(a)esat.kuleuven.be<mailto:Siamak.Mehrkanoon@esat.kuleuven.be> IMPORTANT DATES Extended Submission Deadline: 01/07/2018 Notification Of Acceptance: 31/08/2018 https://tnsre.embs.org/2018/04/13/call-for-papers-special-issue-on-neural-s…) - - - Dr Steve Mehrkanoon Mathematical Neuroscientist, Advance Queensland Research Fellow, Perinatal Research Centre, Faculty of Medicine, Home: http://researchers.uq.edu.au/researcher/14135 Level 4, UQ Centre for Clinical Research, Building 71/918<https://www.google.com.au/maps/place/UQCCR/@-27.448514,153.028703,15z/data=…> Royal Brisbane and Women’s Hospital, Qld 4029 T: +61 7 3346 6012 E: s.mehrkanoon(a)uq.edu.au<mailto:j.wixey@uq.edu.au>

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PhD Position available: Computational methods for longitudinal studies of structural brain connectivity, Deadline 31/5/18
by Emanuele Olivetti May 28, 2018

May 28, 2018

PhD position available (online application details below) Title: Computational methods for longitudinal studies of structural brain connectivity Topic: machine learning / pattern recognition for diffusion MRI data analysis Description: Diffusion MRI provides indirect information of the anatomical structure of the white matter of the brain. Neurological diseases and brain disorders may introduce alterations in such structures. Additionally, after neurosurgery and cognitive rehabilitation, there may be reorganization of the white matter. The goal of this project is to design computational methods to detect and characterize white matter changes over time, disentangling the intrinsic variability of brain recordings from actual anatomical changes, in order to support neuroscientific and clinical inference. References: - https://doi.org/10.3389/fnins.2016.00554 - https://doi.org/10.3389/fnins.2017.00754 Emanuele Olivetti ---------- Forwarded message ---------- From: *PhD CIMeC* <phd.cimec(a)unitn.it <mailto:phd.cimec@unitn.it>> Date: Thu, May 24, 2018 at 10:04 AM Subject: PhD Position available: Computational methods for longitudinal studies of structural brain connectivity, Deadline 31/5/18 To: CIMeC is pleased to announce the opening of a call for 11 fellowships for our international PhD Program in Cognitive and Brain Sciences (CIMeC), commencing November 2018 at the University of Trento, Italy. As you will see from the links below, the PhD call is open to several fields of cognitive neuroscience research. Candidates interested in*Computational methods for longitudinal studies of structural brain connectivity <http://www.unitn.it/drcimec/topic-specific-grants> *should contact *Emanuele Olivetti *at olivetti(a)fbk.eu <mailto:olivetti@fbk.eu>**immediately*.* * *Admissions*: http://www.unitn.it/drcimec/admission <http://www.unitn.it/drcimec/admission> * PhD research areas outline: http://www.unitn.it/drcimec/research-topics <http://www.unitn.it/drcimec/research-topics> * PhD Application*summary*: http://www.unitn.it/drcimec/node/118 <http://www.unitn.it/drcimec/node/118> * PhD*Application*link:https://webapps.unitn.it/Apply/en/MyUnitn/Home/669/dott/cbs34 <https://webapps.unitn.it/Apply/en/MyUnitn/Home/669/dott/cbs34> * PhD Application*Deadline*:*Thursday May 31, 2018, at 4pm (Italian time)* * *CIMeC*:http://www.unitn.it/cimec <http://www.unitn.it/cimec> This year’s research topics proposed by the Doctoral Program Committee for 5 UNITN grants are visible here:http://www.unitn.it/drcimec/research-topics <http://www.unitn.it/drcimec/research-topics>, while the 6 topic-specific grants’ details can be found here:http://www.unitn.it/drcimec/topic-specific-grants <http://www.unitn.it/drcimec/topic-specific-grants> _The CIMeC, it’s doctoral program and UNITN in numbers:_ * 2018 UNITrento ranks among top Italian Universities in THE - Times Higher Education * *4-yr program*(Nov. 1, 2018- Oct. 31, 2022). * Why a 4-yr program <http://www.unitn.it/drcimec/node/117> * Courses are given in English * 11 positions, 100% funded * Salary: starting at approximately €1.200/mo., net * Winners receive a €4887 tax-free research/mobility budget * Why choose UNITRENTO <http://www.unitn.it/en/ateneo/1629/why-choose-the-university-of-trento> Please feel free to browse theFAQ <http://www.unitn.it/drcimec/node/122>pages on our website for further information, or contact the Director of the Programme, Prof. Francesco Pavaniphd.cimec(a)unitn.it <mailto:phd.cimec@unitn.it>. Regards, Leah Mercanti -- Leah Mercanti CIMeC PhD Program Administrator -------------------------------------------------------- CIMeC - Center for Mind/Brain Sciences University of Trento <https://maps.google.com/?q=Trento+Corso+Bettini,+31+I-38068,+Rovereto&entry…> Corso Bettini, 31 <https://maps.google.com/?q=Trento+Corso+Bettini,+31+I-38068,+Rovereto&entry…> I-38068, Rovereto <https://maps.google.com/?q=Trento+Corso+Bettini,+31+I-38068,+Rovereto&entry…> (TN) Tel: +39 0464 80 8617 Fax: +39 0461 28 8690 Skypename: lleahhatwork Email: phd.cimec(a)unitn.it <mailto:phd.cimec@unitn.it> http://www.unitn.it/drcimec/ -- Le informazioni contenute nella presente comunicazione sono di natura privata e come tali sono da considerarsi riservate ed indirizzate esclusivamente ai destinatari indicati e per le finalità strettamente legate al relativo contenuto. Se avete ricevuto questo messaggio per errore, vi preghiamo di eliminarlo e di inviare una comunicazione all’indirizzo e-mail del mittente. -- The information transmitted is intended only for the person or entity to which it is addressed and may contain confidential and/or privileged material. If you received this in error, please contact the sender and delete the material.

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Professorship in Computational Neuroscience
by Steuber, Volker May 25, 2018

May 25, 2018

Professor of Computational Neuroscience University of Hertfordshire School of Computer Science, College Lane Campus, Hatfield, UK Salary £58,293 to £67,437 pa depending on skills and experience FTE: Full time position working 37 hours per week (1.0 FTE). Closing date: 21 June 2018 Duration of Contract: Permanent. Applications are invited for an exceptionally well qualified Professor of Computational Neuroscience of international standing, who shares our commitment to research-informed teaching, embraces the research impact agenda, and values collegiality. Applicants will strengthen existing activity within the School and develop it further, enhancing the research strengths and external reputation of the School of Computer Science and contributing significantly to its performance in future research assessments and collaborations with commercial and public partners. The successful applicant will complement the research conducted by the Biocomputation Research Group within the Centre for Computer Science and Informatics Research. As well as providing research supervision at PhD and MSc level, the School of Computer Science offers modules in neural computing and machine learning on the BSc and MSc programmes. Applicants must hold a PhD (or equivalent) in a relevant subject, possess excellent communication skills in English, an internationally excellent research record and reputation, including publications of the highest quality suitable for submission to the REF. Applicants must show evidence of experience and success in research/commercial income generation, engagement with the research impact agenda, engagement with key stakeholders in the Computational Neuroscience community, and management and leadership ability.? Interview Date: Week commencing 17 September 2018. The University offers a range of benefits including a pension scheme, professional development, family friendly policies, child care vouchers, a fee waiver of 50% for all children of staff under the age of 21 at the start of the course, discounted memberships at the Hertfordshire Sports Village and generous annual leave. The University is situated in Hatfield, in the green belt just north of London. Applications must be made online https://www.herts.ac.uk/contact-us/jobs-and-vacancies/academic-vacancies?, reference 016195?. For informal enquiries contact Dr Volker Steuber (v.steuber(a)herts.ac.uk, Head of Biocomputation Research Group, Associate Dean Research) or Prof William Clocksin (w.clocksin(a)herts.ac.uk, Dean of School of Computer Science).

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