July 2020 - Comp-neuro - lists.cnsorg.org

Professorship position in explainable/interpretable Machine Learning
by Jörg Lücke July 15, 2020

July 15, 2020

Dear list, Let me draw your attention to a currently advertised position on explainable / interpretable learning algorithms. The position is in the Health Sciences but researchers with a data analysis background interested in developing in the direction of health data analysis are of interest. Also candidates with a computational neuroscience background or a robotics background are of interest. So the spectrum of potential candidate profiles is relatively broad. Please see the following link for the official advertisement. https://uol.de/stellen/?stelle=67364 The position is a German W2 Professorship position (similar Associate Professor). Thanks and best wishes, Jörg Lücke -- Jörg Lücke (PhD) Professor and Head of the Machine Learning Lab Department of Medical Physics and Acoustics School of Medicine and Health Sciences University of Oldenburg 26111 Oldenburg Germany www.uol.de/ml

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CNS*2020 Workshop on "Multi-disciplinary approaches to quantify and model calcium signaling in nervous systems and beyond", July 21-22, 2020 (8.30 am-5 pm BST / GMT+1)
by Maurizio De Pittà July 14, 2020

July 14, 2020

Dear colleagues, Please share it with your contacts. I am delighted to be able to share with you the finalized program of the forthcoming Workshop on "Multi-disciplinary approaches to quantify and model calcium signaling in nervous systems and beyond," July 21-22, 2020 (8.30 am-5 pm BST / GMT+1) as part of the CNS*2020 Virtual Conference. Workshop website: https://sites.google.com/view/cns2020-calcium-workshop/home We are joining together some of the prominent scientists in the field, touching a whole range of topics and approaches, ranging from techniques and machine learning tools to acquire calcium signals in living systems, to modeling in neurons, synapses, glial and other systems of the body. Confirmed speakers (in alphabetical order): Amit Agarwal, Heidelberg University, Germany Johnatan Aljadeff, University of California at San Diego, USA Alexey Brazhe, Lomonosov Moscow State University, Russia Pengxing Cao, School of Mathematics and Statistics, University of Melbourne, Australia Evan Cresswell-Clay, National Institute of Health, USA & The Basque Center for Applied Mathematics, Spain Silvina Ponce Dawson, Department of Physics, FCEN-UBA & IFIBA, CONICET-UBA, University of Buenos Aires, Argentina Martin Falcke, Max Delbrück Center for Molecular Medicine Berlin, Germany Johannes Friedrich, Simons Foundation, USA Andrea Giovannucci, UNC-Chapel Hill/North Carolina State University, USA Michael Graupner, Université de Paris, CNRS, SPPIN, France Shawn Means, School of Natural and Computer Sciences, Massey University, New Zealand Vijai Rajagopal, University of Melbourne, AUS Leonid Savtchenko & Dimitri Rusakov, Queen Square Institute of Neurology, University College London, UK Simon Schultz, Centre for Neurotechnology and Department of Bioengineering, Imperial College London, UK Alexey Semyanov, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia Ivo Siekmann, Department of Applied Mathematics, Liverpool John Moores University, UK Alexander Skupin, University of Luxembourg, Luxembourg James Sneyd, The University of Auckland, New Zealand Ghanim Ullah, University of South Florida, USA Agne Tilūnaitė, School of Mathematics and Statistics, University of Melbourne, Australia Ruediger Thul, The University of Nottingham, UK Attendance to the online Workshop is FREE but requires registration to the CNS*2020 meeting (this year free of charge). More Info: https://docs.google.com/document/d/1N45m5I4lZ4wUX4kOkxgPqEK4yeIdADuKgdqPuBF… Schedule of the Workshop's talks, along with Crowdcast links for individual sessions may be found on the Sched page of CNS*2020: https://cns2020online.sched.com/overview/type/Workshop/W02%3A+Calcium+signa… CALCIUM WORKSHOP webpage: https://sites.google.com/view/cns2020-calcium-workshop/home Thank you for your consideration. The workshop organizers: Pengxing Cao, University of Melbourne, Australia Maurizio De Pitta, Basque Center for Applied Mathematics, Spain Ivo Siekmann, Liverpool John Moores University, UK ----- Maurizio De Pitta' Research Fellow MCEN -- Group of Mathematical, Computational and Experimental Neuroscience BCAM -- Basque Center of Applied Mathematics https://sites.google.com/site/mauriziodepitta/home

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Postdoc position at the Research Center Juelich
by Daun, Silvia July 13, 2020

July 13, 2020

Dear All, I have a Postdoc postion to offer in my lab: "Researchers at the subinstitute Cognitive Neuroscience (INM-3) investigate the neural mechanisms underlying cognitive (dys-) function in healthy subjects and patients suffering from neurological and psychiatric disorders. Functional imaging (PET, MRI) and electrophysiological methods (EEG, TMS, tDCS) are combined with computational approaches. The successful candidate will investigate how neural information processing within the human motor system is impaired by (non-)pathological aging under the supervision of Prof. Dr. Silvia Daun. We are looking to recruit a Postdoc - Cognitive Neuroscience / Computational Neurology at the Research Center Juelich Your Job: • Design, acquisition and analysis of EEG data from healthy subjects and stroke patients • Development of analysis algorithms and mathematical models • Presentation and publication of the results • Interaction with team members and collaborators from Psychology, Medicine, and Computational Neuroscience Your Profile: • Completed study in Computer Science, Computational Neuroscience, Physics, Mathematics, Biomedical Engineering including an excellent doctoral degree • Significant programming skills (preferably in Matlab or Python) • Keen interest in cognitive and systems neuroscience • Experience with the conduction of EEG experiments • Proven scientific achievements as evidenced by publications in international, peer-reviewed journals • Interest in combining basic research and translational research on stroke patients • Good command of English • High social competence and organizational talent • High motivation Our Offer: • Exciting working environment on an attractive research campus with excellent infrastructure, located between the cities of Cologne, Düsseldorf, and Aachen • A stimulating, collaborative, and international research environment • A comprehensive further training programme • Flexible working hours and various opportunities to reconcile work and private life • Full-time position with the option of slightly reduced working hours • Limited for 3 years with possible longer-term prospects • Salary and social benefits in conformity with the provisions of the Collective Agreement for the Civil Service (TVöD). Depending on the applicant`s qualifications and the precise nature of the tasks, salary grade EG 13 TVöD-Bund Forschungszentrum Jülich promotes equal opportunities and diversity in its employment relations. We also welcome applications from disabled persons." To apply, please follow the link: https://www.fz-juelich.de/SharedDocs/Stellenangebote/_common/dna/2020-212-E… All the best, Silvia Prof. Dr. rer. nat. Silvia Daun Kognitive Neurowissenschaften Institut für Neurowissenschaften und Medizin (INM-3) Forschungszentrum Jülich Leo-Brandt-Str. 5 52425 Jülich Telefon: 02461-61-8638 Telefax: 02461-61-9853 Email: s.daun(a)fz-juelich.de und Professorin für Computational Neuroscience - Modeling Neural Network Function Zoologisches Institut Universität zu Köln Biowissenschaftliches Zentrum, Zi. 1.104 Zülpicher-Straße 47b 50674 Köln Telefon: 0221-470-3829 Telefax: 0221-470-4889 Email: silvia.daun(a)uni-koeln.de http://www.neuro.uni-koeln.de/neuro-gruhn-staff-sg.html ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ Forschungszentrum Juelich GmbH 52425 Juelich Sitz der Gesellschaft: Juelich Eingetragen im Handelsregister des Amtsgerichts Dueren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Volker Rieke Geschaeftsfuehrung: Prof. Dr.-Ing. Wolfgang Marquardt (Vorsitzender), Karsten Beneke (stellv. Vorsitzender), Prof. Dr.-Ing. Harald Bolt ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------

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job post: machine learning research scientist at NIMH
by Francisco Pereira July 12, 2020

July 12, 2020

*** HIRING: machine learning research scientist The Machine Learning Team at the National Institute of Mental Health (NIMH) in Bethesda, MD, has an open position for a machine learning research scientist. The NIMH is the lead federal agency for research on mental disorders and neuroscience, and part of the National Institutes of Health (NIH). *** About the NIMH Machine Learning Team Our mission is to help NIMH scientists use machine learning methods to address a diverse set of research problems in clinical and cognitive psychology and neuroscience. These range from identifying biomarkers for aiding diagnoses to creating and testing models of mental processes in healthy subjects. We work with many different data types, including very large brain imaging datasets from various imaging modalities, behavioral data, and picture and text corpora. We have excellent computational resources, both of our own (tens of GPUs for deep learning) and shared within the NIH (a cluster with hundreds of thousands of CPUs, and hundreds of GPUs). As a machine learning research group, we develop new methods and publish in the main machine learning conferences (e.g. NeurIPS and ICLR), as well as in psychology and neuroscience journals. Many of our problems require devising research approaches that combine imaging and non-imaging data, and leveraging structured knowledge resources (databases, scientific literature, etc) to generate explanations and hypotheses. You can find more about our work and publications at https://cmn.nimh.nih.gov/mlt *** About the position We are seeking candidates who are capable of combining machine learning, statistical, and domain-specific computational tools to solve practical data analysis challenges (e.g. designing experiments, generating and testing statistical hypotheses, training and interpreting predictive models, and developing novel models and methods). Additionally, candidates should be capable of visualizing and communicating findings to a broad scientific audience, as well as explaining the details of relevant methods to researchers in a variety of domains. Desirable experience that is not required, but will be considered very favorably: - neuroimaging data processing and analysis (any MRI modality, as well as MEG and EEG) - other types of neural data (e.g. neural recording, calcium imaging) - modelling of human and animal learning and decision-making - Bayesian statistical modelling Finally, you should have demonstrable experience coding in languages currently used in data-intensive, scientific computing, such as Python, MATLAB or R. Experience with handling large datasets in high performance computing settings is also very valuable. Although this position requires a Ph.D. in a STEM discipline, we will consider applicants from a variety of backgrounds, as their research experience is the most important factor. This is an ideal position for someone who wants to establish a research career in method development and applications driven by scientific and clinical needs. Given our access to a variety of collaborators and large or unique datasets, there is ample opportunity to match research interests with novel research problems. We also maintain collaborations outside of the NIH, driven by our own research interests. If you would like to be considered for this position, please send francisco.pereira(a)nih.gov a CV, with your email serving as cover letter. If you already have a research statement, please feel free to send that as well. There is no need for reference letters at this stage. Other inquiries are also welcome. Thank you for your attention and interest!

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Two Research (PhD) Positions in Machine Learning Theory and Applications - Oldenburg University, Germany
by Jörg Lücke July 10, 2020

July 10, 2020

The Machine Learning Lab at the University of Oldenburg, Germany, is seeking to fill two positions for doctoral researchers Our Machine Learning Lab conducts mathematically grounded research on novel approaches in Machine Learning with a focus on probabilistic generative approaches including deep generative models. Examples are deep variational autoencoders, deep mixture models, and Bayesian networks. Our research projects are conducted in collaboration with leading international labs, and we publish in leading international journals and present on leading conferences. Our interests are in understanding methods and in developing novel approaches to solve difficult problems in Machine Learning. We are interested in problems with strong data corruptions, strong noise and in problems with few data or few labels. Furthermore, we are in general interested in the development of novel approaches that significantly improve learning efficiency (with applications to Big Data). At the same time, we model neural information processing using Machine Learning models in order to understand the nature of biological intelligence. The two positions will both allow for basic research, and they will both allow for applications to data for tasks such as data enhancement (denoising, inpainting, deblurring), unsupervised and semi-supervised learning, super-resolution, outlier detection etc. Part of one position has a focus on addressing such tasks for medical data. Ideal candidates have a strong background in a theoretical subject and/or a high interest in further advancing Machine Learning methods such as variational optimization. Example degrees that qualify for the positions are degrees in Physics, Mathematics, Statistics, in the Data Sciences or degrees of related disciplines. Strong programming skills are a big plus. Candidates have to hold a MSc degree or have to be sufficiently close to obtaining one. Interested researchers are invited to apply for both positions simultaneously (please indicate in the cover letter). This is an informal description of the positions. The only officially relevant descriptions can be found here (please follow the instructions therein): https://uol.de/stellen/?stelle=67425 https://uol.de/stellen/?stelle=67430 Both positions are funded for 2.5 / 3 years with an intention for extensions. Oldenburg is a nice and affordable place to live, and is located within 40mins travel time of the North Sea coast. It is part of the Bremen/Oldenburg metropolitan region of Germany with close cultural and academic links to Dutch cities like Groningen across the German/Dutch border. The application deadline for the positions is July 19, 2020. -- Prof. Dr. Jörg Lücke Leiter Abteilung Machine Learning Department für Medizinische Physik und Akustik Fakultät für Medizin und Gesundheitswissenschaften Carl von Ossietzky Universität Oldenburg D-26111 Oldenburg www.uol.de/ml

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Workshop: Open data, tools, and models from the Allen Institute supporting systematic computational studies in neuroscience
by Anton Arkhipov July 10, 2020

July 10, 2020

Dear Colleagues, The Workshop “Open data, tools, and models from the Allen Institute supporting systematic computational studies in neuroscience” will take place online on July 21-23, 2020, as a part of the 29th Annual Computational Neuroscience Meeting (CNS*2020). Join us at the Workshop to learn about unique open datasets, software tools, and computational models from the Allen Institute and to discuss how the community can utilize these free resources to support and inform computational and theoretical work. To attend, please register for CNS*2020 at https://www.cnsorg.org/cns-2020 <https://www.cnsorg.org/cns-2020%0b>The registration is free. When: July 21-23, 2020, 8:00am-12:00pm, Pacific Time Workshop Reference: W6 Workshop Organizers: Anton Arkhipov (Allen Institute for Brain Science, Seattle, WA) Saskia de Vries (Allen Institute for Brain Science, Seattle, WA) Nuno da Costa (Allen Institute for Brain Science, Seattle, WA) Confirmed Speakers: Michael Buice (Allen Institute for Brain Science, Seattle, WA) Forrest Collman (Allen Institute for Brain Science, Seattle, WA) Eva Dyer (Georgia Tech, Atlanta, GA) Gaute Einevoll (University of Oslo, Oslo, Norway) Michael Hawrylycz (Allen Institute for Brain Science, Seattle, WA) Tim Jarsky (Allen Institute for Brain Science, Seattle, WA) Jerome Lecoq (Allen Institute for Brain Science, Seattle, WA) Gabriela Michel (Janelia Research Campus, Ashburn, VA) Stefan Mihalas (Allen Institute for Brain Science, Seattle, WA) Lydia Ng (Allen Institute for Brain Science, Seattle, WA) Blake Richards (McGill University, Montreal, Canada) Josh Siegle (Allen Institute for Brain Science, Seattle, WA) Bosiljka Tasic (Allen Institute for Brain Science, Seattle, WA) Jennifer Whitesell (Allen Institute for Brain Science, Seattle, WA) Joel Zylberberg (York University, Toronto, Canada) Further details: https://alleninstitute.org/what-we-do/brain-science/events-training/2020-cn… We hope to see you there! Best wishes, Anton. Anton Arkhipov Associate Investigator T: 206.548.8414 [cidimage001.png(a)01D5F0E2.E3F24C00] www.alleninstitute.org<https://nam12.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.alleni…>

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9th International Summer School in Biomedical Engineering (2020)
by Dölker Eva-Maria TU Ilmenau July 9, 2020

July 9, 2020

Dear Colleagues, We are pleased to announce that we have an excellent list of lecturers at the 9th International Summer School in Biomedical Engineering (2020) hold from 5th-11th August 2020 in Augustinerkloster in Erfurt, Germany. The program can be found on the summer school webpage: https://www.tu-ilmenau.de/bmti/wissenschaftliche-veranstaltungen/summer-sch… We are currently accepting PhD students and advanced Master students applications. Registration info can be found at the point “General Information”. Please send any enquiries to Eva-Maria Dölker <eva-maria.doelker(a)tu-ilmenau.de<mailto:eva-maria.doelker@tu-ilmenau.de>>. Best regards, Eva-Maria Dölker Organization of the Summer School

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FENS Workshop on Glial interfaces: Technology & Methods to uncover the 4D glial role in brain function & dysfunction
by Maurizio De Pittà July 9, 2020

July 9, 2020

Dear colleagues, please mark it on your calendar and disseminate among your contacts: https://cslide.ctimeetingtech.com/fens2020/attendee/confcal/show/session/281 This year's FENS Forum of Neuroscience, which will take place online due to the ongoing Covid19 health emergency, will feature a multidisciplinary workshop on "Glial Interfaces: Technology & Methods to uncover the 4D glial role in brain function & dysfunction" on Saturday, July 11, 2020, 9 am-11.30 am (BST: British Summer Time, GMT+1). *** Program at a glance: Multiscale excitation and recording of astrocytes signaling and conductance by nanostructured devices, Valentina Benfenati, National Research Council, CNR-ISOF, Italy, Exposure to graphene oxide alters astrocyte homeostasis and astrocyte-to-neuron communication, Fabrizia Cesca, University of Trieste, Italy. Lessons learned from a tissue-engineered 3D model of the glial scar, Ana Paula Pêgo, Institute for Bioengineering (INEB), and Institute for Research and Innovation in Health (I3S), Portugal. Reverse engineering neuron-glial interactions: An overarching approach from cellular biophysics to medicine, Maurizio De Pitta, Basque Center for Applied Mathematics, Spain. Exploring the structure, neuronal content, and functional significance of astrocytic domains of behaving animals with CLARITY and 2-photon imaging, Adi Doron, The Hebrew University, Israel. The color of pain: Technology advances allowing the future objective quantification, Mark Hutchinson, University of Adelaide, Australia. *** A Live Q&A session will follow the workshop. For further information: https://cslide.ctimeetingtech.com/fens2020/attendee/confcal/show/session/281 Thank you for your consideration. Maurizio De Pitta ----- Maurizio De Pitta' Research Fellow MCEN -- Group of Mathematical, Computational and Experimental Neuroscience BCAM -- Basque Center of Applied Mathematics https://sites.google.com/site/mauriziodepitta/home

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Call for papers: GEM 2021 - workshop on generative episodic memory
by Vinita Samarasinghe July 9, 2020

July 9, 2020

Call For Papers: *GEM 2021**- Generative Episodic Memory: Interdisciplinary perspectives from psychology, neuroscience and philosophy* https://for2812.rub.de/gem2021 16-18 February 2021 /Ruhr University Bochum, Germany/ The DFG-funded research consortium “FOR 2812 – Constructing scenarios of the past” https://for2812.rub.de is proud to announce a call for papers for its first workshop on generative episodic memory. Depending on the public health situation in February next year, the workshop will be in-person, virtual or a hybrid event. We invite submissions for talks and posters https://easychair.org/cfp/gem2021. Episodic memories are widely regarded as memories of personally experienced events. Early concepts about episodic memory were based on the storage model, according to which experiential content is preserved in memory and later retrieved. However, overwhelming empirical evidence suggests that the content of episodic memory is – at least to a certain degree – constructed in the act of remembering. Even though very few contemporary researchers would oppose this view of episodic memory as a generative process, it has not become the standard paradigm of empirical memory research. This is particularly true for studies of the neural correlates of episodic memory. Further hindering progress are large conceptual differences regarding episodic memory across different fields, such as neuroscience, philosophy, and psychology. This interdisciplinary workshop therefore aims to bring together researchers from all relevant fields to advance the state of the art in the research on generative episodic memory. FOR 2812 “Constructing scenarios of the past: A new framework in episodic memory” consists of 9 researchers. Seven from the Ruhr University Bochum and two from the University of Münster. The consortium adopts an interdisciplinary approach and investigates generative episodic memory from a conceptual, modeling, and experimental perspective using a common conceptual framework: scenario construction. Keynote Speakers: Karl-Heinz Bäuml - University Regensburg, Germany Dorthe Berntsen - Aarhus University, Denmark Amy Criss - University of Syracuse, USA Dorothea Debus - University of Konstanz, Germany David Huber - University of Massachusetts, USA Sarah Robins - University of Kansas, USA Deadlines [GMT +1 (CET)]: Abstract submission - 15.11.2020 Notification of acceptance - 19.12.2020 Submission guidelines: Abstracts must be submitted in English and be no longer than 1 page. Submitted work must be original and unpublished. Abstracts must be submitted electronically through the GEM 2021 paper submission site on EasyChair https://easychair.org/cfp/gem2021. Authors will receive confirmation of receipt of their abstracts including an ID number after submission. You can edit your submission at any time before the deadline. We will consider only the final version. Program committee: Nikolai Axmacher - Faculty of Psychology - Ruhr University Bochum Sen Cheng - Institute for Neural Computation - Ruhr University Bochum Gerald Echterhoff - Faculty of Psychology - University of Münster Albert Newen - Faculty of Philosophy - Ruhr University Bochum Ricarda Schubotz - Faculty of Psychology - University of Münster Markus Werning - Faculty of Philosophy - Ruhr University Bochum Laurenz Wiskott - Institute for Neural Computation - Ruhr University Bochum Oliver Wolf - Faculty of Psychology - Ruhr University Bochum All questions regarding the workshop should be emailed to for2812(a)rub.de Coordinator - Vinita Samarasinghe Secretary - Christiane Dahl -- Vinita Samarasinghe M.Sc., M.A. Science Manager Arbeitsgruppe Computational Neuroscience Institut für Neuroinformatik Ruhr-Universität Bochum, NB 3/26 Postfachnummer 110 Universitätstr. 150 44801 Bochum Tel: +49 (0) 234 32 27996 Email: samarasinghe(a)ini.rub.de

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Fully funded Ph.D. Studentship in Cognitive Computational Neuroscience
by Wong-Lin, Kongfatt July 8, 2020

July 8, 2020

Applications are invited for a fully funded 3-year Ph.D. studentship in Cognitive Computational Neuroscience at Ulster University, UK. This Ph.D. project aims to develop computational modelling techniques to understand brain and behavioural data across primate species, and to apply techniques in computational neuroscience particularly biologically based neural network modelling to elucidate the mechanisms underlying abstract decision making. This Ph.D. project is part of an externally funded international collaboration: Prof. Michael Shadlen at Columbia University (USA), Prof. Stephan Bickel at Northwell-Hofstra School of Medicine (USA), Prof. Redmond O'Connell at Trinity College Dublin (Ireland), Prof. Simon Kelly at University College Dublin (Ireland), and Dr. KongFatt Wong-Lin at Ulster University (UK). Some relevant references: (i) O'Connell RG, Shadlen MN, Wong-Lin K, Kelly SP. Bridging Neural and Computational Viewpoints on Perceptual Decision-Making. Trends Neurosci. 2018;41(11):838‐852. doi:10.1016/j.tins.2018.06.005 (ii) Atiya NAA, Rañó I, Prasad G, Wong-Lin K. A neural circuit model of decision uncertainty and change-of-mind. Nat Commun. 2019;10(1):2287. doi:10.1038/s41467-019-10316-8 (iii) O'Connell RG, Dockree PM, Kelly SP. A supramodal accumulation-to-bound signal that determines perceptual decisions in humans. Nat Neurosci. 2012;15(12):1729‐1735. doi:10.1038/nn.3248 This timely and exciting project is available in the Computer Science Research Institute and is tenable in the Faculty of Computing, Engineering and the Built Environment at Magee Campus. The successful Ph.D. candidate will benefit from the expertise of Ulster’s Cognitive and Computational Neuroscience, Machine Learning, and Computational Biology communities, and will interact closely with experimental collaborators. The student will gain valuable skills and knowledge in computational and mathematical modelling, biological signal processing, machine learning, high-performance computing, mathematics/statistics, and brain sciences. All applicants should hold a first or upper second class honours degree (or equivalent) in Physics, Mathematics, Computer Science, Mathematics, Engineering, Statistics, Neuroscience, Biology, or a cognate area. Applications will be considered on a competitive basis with regard to the candidate’s qualifications, skills, experience and interests. Successful candidates will enrol as of 1st January 2021, on a full-time programme of research studies leading to the award of the degree of Doctor of Philosophy. The Ph.D. studentship will comprise fees together with an annual stipend and will be awarded for a period of up to three years subject to satisfactory progress. Additional financial support may be available from research funding. If you wish to discuss your proposal or receive advice on this project please contact: Dr. KongFatt Wong-Lin, email: k.wong-lin(a)ulster.ac.uk . Procedure: For more information on applying: https://www.ulster.ac.uk/doctoralcollege Apply online: https://www.ulster.ac.uk/doctoralcollege/find-a-phd?type=funded The closing date for receipt of completed applications is 31st August 2020. Interviews will be held in September 2020, and starting date is on 1st January 2021. ------------------- Dr. KongFatt Wong-Lin Reader Intelligent Systems Research Centre School of Computing, Engineering and Intelligent Systems Ulster University, UK https://www.ulster.ac.uk/staff/k-wong-lin 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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