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Research Associate in Functional Brain Mapping
by Wong-Lin, Kongfatt March 20, 2017

March 20, 2017

Research Associate in Functional Brain Mapping Applications are invited for a Post-Doctoral Research Associate (PDRA) in functional brain mapping (FBM) to work on a project aimed at discovering neuromarkers that facilitate stratification of patients with Alzheimer´s disease. The position is currently for 2 years, with possibility for further extension subject to securing funder’s approval. Job Ref at http://www.ulster.ac.uk/jobs: 1632872 Salary: £26,844 to £39,347 Closing Date: 4th April 2017 Duties The successful candidate will use MEG data recorded during cognitive tasks, stimulations, and resting state protocols to explore functional connectivity and other appropriate measures for characterizing individuals with different stages of AD and detecting individuals at the risk of developing AD. S/he will also develop and evaluate methods for assessing treatment effects on individuals with AD in collaboration with industry. Northern Ireland Functional Brain Mapping (NIFBM) facility The NIFBM is located at the Intelligent Systems Research Centre (isrc.ulster.ac.uk<http://isrc.ulster.ac.uk>) of Ulster University, Magee campus, Derry~Londonderry. It is the only brain imaging facility anywhere in Ireland and only one of nine in whole of UK to use a state-of-the-art magnetoencephalography (MEG) to measure brain activity. The facility attracts clinicians and researchers from across Northern Ireland as well as Republic of Ireland. It is equipped with the latest whole head 306 channels Elekta Neuromag MEG TRIUX system, which also includes a 128-channel EEG recording system. We offer several advanced techniques for brain stimulation and analysis that allow us to obtain better results and guarantee a high quality service for both research and clinical applications. The ISRC is a major research unit in the Faculty of Computing and Engineering and hosts around 80 researchers including academic staff, research associates and PhD students organized in four research teams: Neural Systems and Neuro-technology, Computational Neuroscience and Neural Engineering, Cognitive Robotics, and Ambient Intelligence and Virtual Worlds. Based at ISRC, the successful candidate will have an opportunity to interact with researchers from related ISRC teams as well as Biomedical Sciences Research Institute (5* research rating), and the recently developed Centre for Stratified Medicine at Ulster University. Eligibility Requirements An eligible candidate should have a degree in Computing Science, Electronic Engineering, Physics, or a closely related discipline, or a higher degree in the same or related subjects. Applicants with other relevant degrees e.g. medicine, neuroscience or biomedical sciences may also be considered, subject to demonstration of substantial neuroimaging expertise. A PhD degree in an area relevant to the post is also an essential requirement. It is also required that a candidate: * Has extensive hands-on MEG experience including protocol design, setting up experiments and stimulations, and data acquisition; * Has strong skills and expertise in MEG analysis using modern tools such as Fieldtrip, SPM, MNE, and/or Brainstorm; * Has research track record in cognitive neuroscience and/or Alzheimer’s disease supported by at least two high quality journal publications suitable for submission in to UK’s Research Excellence Framework (REF); * Is a self-motivated individual, enjoys working in a team and interacting with researchers and study participants. Please apply on-line by visiting either our university web-site http://www.ulster.ac.uk/jobs or the advertisement appearing at: http://www.jobs.ac.uk/job/AXT197/research-associate-in-functional-brain-map… For more information, please contact Prof. Girijesh Prasad, Principal Investigator & Director NIFBM. E-mail: g.prasad(a)ulster.ac.uk<mailto:g.prasad@ulster.ac.uk>, Phone: 028 71675645. This email and any attachments are confidential and intended solely for the use of the addressee and may contain information which is covered by legal, professional or other privilege. If you have received this email in error please notify the system manager at postmaster(a)ulster.ac.uk and delete this email immediately. Any views or opinions expressed are solely those of the author and do not necessarily represent those of Ulster University. The University's computer systems may be monitored and communications carried out on them may be recorded to secure the effective operation of the system and for other lawful purposes. Ulster University does not guarantee that this email or any attachments are free from viruses or 100% secure. Unless expressly stated in the body of a separate attachment, the text of email is not intended to form a binding contract. Correspondence to and from the University may be subject to requests for disclosure by 3rd parties under relevant legislation. The Ulster University was founded by Royal Charter in 1984 and is registered with company number RC000726 and VAT registered number GB672390524.The primary contact address for Ulster University in Northern Ireland is Cromore Road, Coleraine, Co. Londonderry BT52 1SA

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Course announcement: CAMP@Bangalore 2017
by Sahil Moza March 20, 2017

March 20, 2017

We would like to announce CAMP@Bangalore 2017 from 19 July 2017 to 3 August 2017. Please see the course website at http://camp.ncbs.res.in/ CAMP @ Bangalore (Computational Approaches to Memory and Plasticity at NCBS, Bangalore) is a 16-day summer school on the theory and simulation of learning, memory and plasticity in the brain. The course consists of four modules covering sub-cellular electrical models, micro-circuits and network models, detailed models with electrical and chemical components, and systems level models, all with an emphasis on learning, memory and plasticity. All modules will have their own hands-on projects. Students worldwide are encouraged to apply. Accommodation and food will be free for the selected students. There is no registration fee. Students are advised to obtain independent travel grants. Confirmed instructors include: Andrew Holmes (National Institutes of Health, Bethesda, Maryland) Arvind Kumar (KTH, Stockholm) Avrama Kim Blackwell (George Mason University, Virginia) Joshua A. Gordon (National Institute of Mental Health, Bethesda, Maryland Rishikesh Narayanan (Indian Institute of Science, Bangalore) Sachin Deshmukh ( Indian Institute of Science, Bengaluru) Suhita Nadkarni (Indian Institute of Science Education and Research, Pune) Sumantra Chattarji (NCBS, Bangalore) Upinder Bhalla (NCBS, Bangalore) Course Organizers: Upinder Bhalla (NCBS, Bangalore) Arvind Kumar (KTH Stockholm) Rishikesh Narayanan (Indian Institute of Science, Bangalore) -- Sahil Moza PhD student National Centre for Biological Sciences, TIFR, Bangalore, India

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Postdoc positions in Neuromorphic computing in Singapore
by Yansong Chua March 20, 2017

March 20, 2017

Multiple scientist and research engineer positions are available in Singapore, at the Institute for Infocomm Research (I2R), A*STAR, Singapore. This project is part of a large multidisciplinary grant in neuromorphic technologies involving multiple universities and research institutions in Singapore (NUS, NTU, IME, IHPC, I2R). The project is focused on building a new neuromorphic chip using RRAM that enables on-chip learning, together with a suite of learning algorithms that would then be deployed in applications in the advanced manufacturing domain. The total grant is for 4 years, with a budget of S$25,000,000. The primary scope of our research is to develop spike-based computing and learning algorithms for deep spiking neural networks on a neuromorphic chip. Specifically, we are interested in employing spikes in information processing and learning. To this end, successful candidates will conduct research in one or more of the following areas: - Neuronal coding. What coding and readout strategy underlie spike-based representation. How to encode external stimuli into spike based representations and how to readout information from spike activities. - Learning. How does neurons adapt their synaptic weights to perform a given task under cases of supervised, unsupervised and reinforcement signals. What are the underlying mechanisms for deep-structured network learning. - System integration and applications. How to integrate different computational principles into a system and apply it to solve different practical tasks. Two particular focus of research are: - Deep reinforcement learning on a neuromorphic platform for the control of robots deployed in the advanced manufacturing domain - Compressing and mapping of state-of-art deep learning networks onto a neuromorphic platform, for either inference (only) or both training and inference. Preference will be given to candidates who can document knowledge in machine learning, neural networks, information processing, system design or hardware implementation with VLSI and FPGA. Candidates must have a PhD (for scientists) or MS/BS (for engineers) in computer science, computational neuroscience or related fields. Strong programming and quantitative skills are highly desired. Candidates should be proficient in spoken and written English. The appointments will be for 3 years, and extended for another 1 year, after review. Salaries are commensurate with internationally-competitive salaries and benefits. The start date is flexible and applications will be considered on a rolling basis until the positions are filled. Other benefits include: - Funding for international conferences and training courses - Collaboration opportunities with an excellent network of international scientists Candidates please send your curriculum vitae, a statement of research interests and three references to Dr. Yansong Chua (chuays(a)i2r.a-star.edu.sg) or Dr. Qiang Yu (yuqiang(a)i2r.a-star.edu.sg) More information: - Institute for Infocomm Research: http://www.i2r.a-star.edu.sg/ - Working in Singapore: http://www.contactsingapore.sg/ professionals/why_singapore/

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faculty position
by Canavier, Carmen C. March 17, 2017

March 17, 2017

The Department of Cell Biology and Anatomy at the Louisiana State University Health Sciences Center, School of Medicine in New Orleans is seeking a full-time academic faculty member at the rank of Assistant to Associate Professor– Research in neurobiology on the non-tenure track. Departmental research strengths include, but are not limited to, synaptic physiology, electrophysiology, and computational neuroscience. The Centers of Excellence in Neuroscience, Alcohol and Drug Abuse, Cancer, and Cardiovascular Biology provide additional collaborative opportunities. The successful candidate is expected to work independently, as well as collaboratively, using existing shared departmental resources for routine molecular biology, cell microscopy, RNAscope, and a Linux cluster. Candidates must have a clear vision on how to maintain (or establish) a funded research program, as well as the skills and publication record to support this vision utilizing the resources available in the department. Qualifications * Ph.D, M.D. or M.D./Ph.D * Postdoctoral experience and a publication record commensurate with experience level About the School Additional information about the department and faculty is available on the LSUHSC website: http://www.medschool.lsuhsc.edu/cell_biology/ Applicant Instructions Candidates must submit a cover letter, current curriculum vitae, summary of research plans and contact information for 3-4 professional references in a single file attachment. You must apply online at https://www.lsuhsc.edu/Administration/hrm/CareerOpportunities/Home/Detail/1…

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Cajal Course in Computational Neuroscience: Deadline March 27
by Jakob Macke March 17, 2017

March 17, 2017

CAJAL COURSE IN COMPUTATIONAL NEUROSCIENCE 6-26 August 2017, Champalimaud Centre for the Unknown, Lisbon, Portugal http://www.cccn.pt We have extended the application deadline to 27 March 2017 (midnight, CET time). DIRECTORS • Gilles Laurent (MPI Brain Research, Frankfurt, Germany) • Jakob Macke (Research Center Caesar, an associate of the Max Planck Society, Bonn, Germany) • Christian Machens (Champalimaud Centre for the Unknown, Portugal) Computational Neuroscience is a rapidly evolving field whose methods and techniques are critical for understanding and modelling the brain, and also for designing and interpreting experiments. Mathematical modeling is an essential tool to cut through the vast complexity of neurobiological systems and their many interacting elements. This three-weeks school teaches the central ideas, methods, and practice of modern computational neuroscience through a combination of lectures and hands-on project work. Each morning is devoted to lectures given by distinguished international faculty on topics across the breadth of experimental and computational neuroscience. During the rest of the day, students work on research projects in teams of 2-3 people under the close supervision of expert tutors and faculty. Research projects will be proposed by faculty before the course, and will include the modeling of neurons, neural systems, and behavior, the analysis of state-of-the-art neural data (behavioral data, multi-electrode recordings, calcium imaging data, connectomics data, etc.), and the development of theories to explain experimental observations. The course is designed for graduate students and postdoctoral fellows from a variety of disciplines, including neuroscience, physics, electrical engineering, computer science, mathematics and psychology. Students are expected to have a keen interest and basic background in neurobiology, a solid foundation in mathematics, as well as some computer experience. A four-day pre-school in mathematics and programming is offered for students that want to catch up on their math and programming skills. A maximum of 24 students will be accepted. Students of any nationality can apply. We specifically encourage applications from researchers who work in the developing world. Stipends are available. More information on the course website, http://www.ccn.pt Apply here: http://www.fens.org/Training/CAJAL-programme/CAJAL-Courses-2017/CCCN2017/ Contact address: Simone Zacarias, simone.zacarias(a)research.fchampalimaud.org Faculty: Alberto Bernacchia University of Cambridge, UK Claudia Clopath Imperial College London, UK Anne Collins Helen Wills Neuroscience Institute, UC Berkeley, USA Sophie Denève Institut d'Etudes de la Cognition (IEC), France Rainer Engelken Max Planck, Goettingen, Germany David Fitzpatrick Max-Planck Florida Institute for Neuroscience, USA Julijana Gjorgjieva Max Planck Institute for Brain Research, Germany Pedro J. Gonçalves Research Center Caesar, Associate of Max Planck Society, Germany Richard Hahnloser Institute of Neuroinformatics, ETH Zurich, Switzerland Michael Häusser Wolfson Institute for Biomedical Research, University College London, UK Andreas Herz Bernstein Center for Computational Neuroscience Munich, Germany Matthias Kaschube Frankfurt Institute for Advanced studies, Germany Simon Laughlin University of Cambridge, UK Máté Lengyel University of Cambridge, UK Zhaoping Li University College London, UK Jennifer Linden UCL Ear Institute, UK Thomas Mrsic-Flogel Sainsbury Wellcome Centre, University College London, UK Joe Paton Champalimaud Centre for the Unknown, Portugal Astrid Prinz Emory University, USA Maneesh Sahani Gatsby Computational Neuroscience Unit, UCL, UK Thanos Siapas Caltech, USA Tatjana Tchumatchenko Max Planck Institute for Brain Research, Germany Andreas Tolias Baylor College of Medicine, USA Byron Yu Carnegie Mellon University, USA Jakob Macke Max Planck Research Group Leader Neural Systems Analysis research center caesar www.mackelab.org

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PhD position in Computational Neuroscience, Ruben Moreno-Bote Lab, Barcelona, Spain
by Ruben Moreno Bote March 17, 2017

March 17, 2017

*PhD Position in* *Computational Neuroscience, Ruben Moreno-Bote Lab* *Center for Brain and Cognition, University Pompeu Fabra, Barcelona, Spain* 1 fully funded PhD position is available in the group of Theoretical and Cognitive Neuroscience of Ruben Moreno-Bote in the Center for Brain and Cognition at the University Pompeu Fabra, Barcelona, Spain. We are looking for excellent candidates with Physics, Mathematics or Machine Learning background, ideally with knowledge of Neuroscience or Computational Neuroscience, and interested in theory and applications. We will also consider candidates with Psychology background interested in mathematical modeling. The candidate will develop state of the art mathematical techniques to understand neuronal dynamics and coding and will have access to multielectrode recording neural data. He/she could also be involved in the design of monkey and human behavioral experiments and the development of models of visual perception, decision making and working memory. The candidate will benefit from the stimulating environment of Barcelona area in Theoretical and Systems Neuroscience and will have the opportunity of enjoying a lively city. Our lab (https://www.upf.edu/web/ruben-moreno-bote) forms part of a larger network of neuroscience labs in Barcelona (http://www.barcelonaneuroscience.com) Financial support is provided by the University Pompeu Fabra, and FLAG-ERA and MINECO grants. APPLICATION : A full CV in pdf format and an extract of grades for degree and master studies should be sent to the following address: ruben.moreno(a)upf.edu DEADLINE: until the position is filled -- Rubén Moreno Bote Serra Húnter Professor Center for Brain and Cognition & Dept. of Information and Communications Technologies University Pompeu Fabra Campus Ciutadella, Building 24, office 331 Ramon Trias Fargas, 24-27 08005 Barcelona, Spain http://www.upf.edu/pdi/ruben-moreno-bote

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MIT-SENIOR UNITY 3D ENGINEER AND PROJECT LEAD
by Christopher Shay March 15, 2017

March 15, 2017

See below for a recently posted Job Opportunity: Job Description: SENIOR UNITY 3D ENGINEER AND PROJECT LEAD, McGovern Institute for Brain Research, to develop and lead a comprehensive Unity-3D-based interactive audio-visual simulation environment for use in training and testing artificial intelligence agents built using deep neural networks. Will join a group of laboratories based at MIT (DiCarlo lab) and Stanford (Yamins lab) that build neural network models of brain data and plan to use large quantities of simulated data to train these models. Primary responsibilities include developing and maintaining core modules for the code base, including high-quality rendering and physics plugins; procuring large numbers of realistic 3D assets for the environment and performing quality assurance to ensure they can be used together; and setting up and maintaining a large-scale, high-availability installation of the environment on a special-purpose Linux cluster. Job Requirements: REQUIRED: bachelor’s degree in computer science or software engineering (master’s in computer graphics or related field preferred); high level of competence in Unity-3D C# and Unity-3D software environments; expertise with a variety of modern rendering procedures, including approximate real-time and high-quality physically-based techniques; expertise in physics simulations, including methods for producing fast approximations to dynamics for complex objects; knowledge of 3D asset libraries and stores and issues with standardizing material properties for rendering and physics; ability to partner with colleagues and independently manage multiple projects/priorities while meeting changing deadlines, adapt to new technologies, and present information in a clear and cohesive manner; creative problem solving skills; ability to approach tasks with an eye toward efficiency and reproducibility; excellent written and oral communications skills; meticulous attention to detail; and proactive approach to investigative analysis. Experience in academic research highly desirable, particularly computational geometry and/or physically-based rendering. Job #14562 Please visit https://careers.mit.edu/ <https://careers.mit.edu/> to apply. Best, Christopher Shay, PhD Lab Manager DiCarlo Lab McGovern Institute Lab: (617) 452-3261 Fax:(617) 253-0104

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IARPA MICrONS Technical Supervisor Position (Washington, DC)
by Alyssa Picchini Schaffer March 15, 2017

March 15, 2017

Please contact David Markowitz if interested: david.markowitz(a)iarpa.gov *Machine Intelligence from Cortical Networks (MICrONS) Technical Supervisor* Despite significant progress in machine learning over the past few years, today’s state of the art algorithms are brittle and do not generalize well. In contrast, the brain is able to robustly separate and categorize signals in the presence of significant noise and non-linear transformations, and can extrapolate from single examples to entire classes of stimuli. This performance gap between software and wetware persists despite some correspondence between the architecture of the leading machine learning algorithms and their biological counterparts in the brain, presumably because the two still differ significantly in the details of operation. The MICrONS program aims to achieve a quantum leap in machine learning by creating novel machine learning algorithms that use neurally-inspired architectures and mathematical abstractions of the representations, transformations, and learning rules employed by the brain. To guide the construction of these algorithms, performers will conduct targeted neuroscience experiments that interrogate the operation of mesoscale cortical computing circuits, taking advantage of emerging tools for high-resolution structural and functional brain mapping. The program is designed to facilitate iterative refinement of algorithms based on a combination of practical, theoretical, and experimental outcomes: performers will use their experiences with the algorithms’ design and performance to reveal gaps in their understanding of cortical computation, and will collect specific neuroscience data to inform new algorithmic implementations that address these limitations. Ultimately, as performers incorporate these insights into successive versions of the machine learning algorithms, they will devise solutions that can achieve human-like performance on complex information processing tasks with human-like proficiency. Position Requirements: Requirement 1: PhD in neuroscience, physics or a related discipline with 4 years of experience studying coding and computation in high-throughput recordings of neural activity from behaving animals using quantitative methods, such as dimensionality reduction, time series analysis, and machine learning approaches. Requirement 2: Demonstrated experience in at least 3 of the following disciplines: high-throughput electrophysiology, multi-photon microscopy, optogenetics, circuit mapping, methods for manipulating cognitive processes in behaving animals. Requirement 3: Training and demonstrated capabilities in applied mathematics and computer science. Must be proficient with at least one numerical analysis and statistics framework (e.g. NumPy, Matlab, R) and one general-purpose programming language (e.g. Python, Java, C). Requirement 4: Two years of experience coordinating collaborative projects with diverse technical contributors and aggressive timelines for achieving results, as evidenced by research publications, public data sets or other artifacts of work. Desired 1: Strong background in systems neuroscience, with at least 2 years of experience studying the circuit basis of cognition. Desired 2: Strong background in machine learning (ML), with at least 2 years of experience using modern ML techniques to support scientific research or solve other challenging problems. Desired 3: Formal training in theoretical neuroscience. Desired 4: Professional software development experience. Desired 5: Experience using cloud computing technologies.

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Bernstein Network Information Booth at 12th Göttingen Meeting of the German Neuroscience Society (NWG)
by Kerstin Schwarzwaelder March 15, 2017

March 15, 2017

Dear colleagues, The Bernstein Network Computational Neuroscience will have an exhibition booth at the upcoming NWG Meeting<https://www.nwg-goettingen.de/2017/default.asp> in Göttingen (March 22 - 25, 2017). Representatives of the Bernstein Network<http://www.nncn.de/en/start_page?set_language=en>, the SMART<http://www.smartstart-compneuro.de/>START training program in Computational Neuroscience<http://www.smartstart-compneuro.de/>, and G-Node<http://www.g-node.org/> will be present at the booth. The booth will present: * research fields * study and training programs * open positions * research and funding opportunities * infrastructural facilities: G-Node<http://www.g-node.org/> and Simulation Laboratory Neuroscience - Bernstein Facility for Simulation and Database Technology<http://www.fz-juelich.de/ias/jsc/EN/Expertise/SimLab/slns/_node.html> Furthermore, the G-Node will present their new data management service<http://www.g-node.org/gin> for storing, sharing, and publishing research data. Demo presentations will be given during poster session times. Conference participants are invited to come by the booth any time to try out the new service. We are looking forward to welcoming you at our booth! Best regards, Kerstin Schwarzwälder -- Dr. Kerstin Schwarzwälder Scientific Coordination / Management Officer Please note: Our email addresses have changed. Please use k.schwarzwaelder(a)fz-juelich.de<mailto:k.schwarzwaelder@fz-juelich.de> Bernstein Network Computational Neuroscience | Bernstein Coordination Site (BCOS) Branch Office of the Forschungszentrum Jülich at the University of Freiburg Hansastr. 9A | 79104 Freiburg, Germany phone: (+49) 0761 203 9589 mail: k.schwarzwaelder(a)fz-juelich.de<mailto:k.schwarzwaelder@fz-juelich.de> web: www.nncn.de<http://www.nncn.de> Twitter: NNCN_Germany<https://twitter.com/NNCN_Germany> YouTube: Bernstein TV<https://www.youtube.com/user/BernsteinNetwork> Facebook: Bernstein Network Computational Neuroscience, Germany<https://www.facebook.com/BernsteinNetwork/> LinkedIn: Bernstein Network Computational Neuroscience, Germany<https://www.linkedin.com/company/bernstein-network-computational-neuroscien…> <https://www.linkedin.com/company/bernstein-network-computational-neuroscien…> ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ Forschungszentrum Juelich GmbH 52425 Juelich Sitz der Gesellschaft: Juelich Eingetragen im Handelsregister des Amtsgerichts Dueren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Dr. Karl Eugen Huthmacher Geschaeftsfuehrung: Prof. Dr.-Ing. Wolfgang Marquardt (Vorsitzender), Karsten Beneke (stellv. Vorsitzender), Prof. Dr.-Ing. Harald Bolt, Prof. Dr. Sebastian M. Schmidt ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------

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PhD in Computational Neuroscience at the University of Exeter (fully funded)
by James Rankin March 15, 2017

March 15, 2017

3.5 year college funded PhD Studentship in Computational Neuroscience: *Neural dynamics of perceptual competition * Ref: 2589 Open to UK, EU and International students with maintenance (£14,296 per year) and tuition fees fully funded http://www.exeter.ac.uk/studying/funding/award/?id=2589 This interdisciplinary project will use mathematical modelling, in conjunction with psychophysics (human perception experiments), to better understand the neural competition underpinning the dynamics of perception. Ambiguity in fixed sensory stimuli can lead to spontaneous switches in perception, both in vision, e.g. binocular rivalry, Necker cube, and audition, e.g. auditory streaming (switches between grouped or segregated interpretations of tone sequences). A set of common characteristics (inevitability of perceptual changes, exclusivity between the competing percepts, and randomness in the percept durations), generalise across sensory modalities. The neural competition driving these perceptual switches has been successfully modelled in small networks of Wilson-Cowan (firing rate) units, each associated with the different perceptual interpretations. For certain stimuli, where competition takes place across a continuous feature space (say, visual orientation, motion direction, or auditory pitch), a continuum model, such as the neural field equation can be applied. This PhD project will involve the derivation of perceptual competition models in a dynamical systems framework, based on plausible neural mechanisms commonly found in sensory cortex. Modelling hypotheses and predictions will be tested against experimental data collected in our lab or from collaborators. On the modelling side, tools from bifurcation analysis including numerical continuation will be applied to investigate dynamics. The project will be flexible in terms of the balance between modelling and experiments. Candidates with quantitative backgrounds (mathematics, physics, and engineering) and from neuroscience or psychology programmes are encouraged to apply. Programming experience and/or knowledge of dynamical systems theory is a plus. Contact: j.a.rankin(a)exeter.ac.uk Informal enquiries welcome. Application deadline: 10th April 2017 Please forward to interested parties as appropriate Thanks, James

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