- Comp-neuro - lists.cnsorg.org

Workshop on Stochastic Neural Computation in Paris
by Wolfgang Maass 13 Aug '14

13 Aug '14

I am organizing a Workshop on Stochastic Neural Computation on Nov.27 and 28, 2014 in Paris, at the European Institute for Theoretical Neuroscience. You are welcome to attend, and present a poster (if it fits into the context of this workshop). This will be a very informal "working" workshop, where we want to bring together experts from neuroscience, cognitive science, theory, and neuromorphic hardware, that are working on different angles of stochastic neural computation with biological or artificial spiking neurons. The talks will focus on new results. We will also have plenty of time to discuss open problems and challenges that arise. Possibly this meeting could mark the beginning of some loose research network around this exciting research topic. You can find a preliminary program at https://flagship.kip.uni-heidelberg.de/jss/Ag?eMAt=38&showAgenda=x&eKn=SCom… Information on the venue and hotel information is available at https://flagship.kip.uni-heidelberg.de/jss/Ag?eMAt=38&SiD=x&eKn=SComNo27 The participation is free, but prior registration by October 1 is required on https://flagship.kip.uni-heidelberg.de/jss/Ag?eMAt=38&eKrn=SComNo27 Under "Registration type" on the registration page you can indicate whether you want to present a poster (please send title and abstract to me per email). There will be no registration fee. best regards Wolfgang Maass -- Prof. Dr. Wolfgang Maass Institut fuer Grundlagen der Informationsverarbeitung Technische Universitaet Graz Inffeldgasse 16b , A-8010 Graz, Austria Tel.: ++43/316/873-5822 Fax ++43/316/873-5805 http://www.igi.tugraz.at/maass/Welcome.html

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Neural plasticity for rich and uncertain robotic information streams, abstract deadline extended 12th September.
by f.vandervelde＠utwente.nl 13 Aug '14

13 Aug '14

Dear All, We extended the abstract submission deadline for the research topic “Neural plasticity for rich and uncertain information streams”, hosted by Frontiers in Neurorobotics, due to requests. The new deadline is 12th of September. Note that the paper submission deadline remains unchanged (Jan 12, 2015). Description: Models of adaptation and neural plasticity are often demonstrated in robotic scenarios with heavily pre-processed and regulated information streams to provide learning algorithms with appropriate, well timed, and meaningful data to match the assumptions of learning rules. On the contrary, natural scenarios are often rich of raw, asynchronous, overlapping and uncertain inputs and outputs whose relationships and meaning are progressively acquired, disambiguated, and used for further learning. Therefore, recent research efforts focus on neural embodied systems that rely less on well timed and pre-processed inputs, but rather extract autonomously relationships and features in time and space. In particular, realistic and more complete models of plasticity must account for delayed rewards, noisy and ambiguous data, emerging and novel input features during online learning. Such approaches model the progressive acquisition of knowledge into neural systems through experience in environments that may be affected by ambiguities, uncertain signals, delays, or novel features. This research topic promises to unveil fundamental properties and dynamics of neural learning system that are naturally immersed in a rich information flow. We invite papers describing advances in robotic neural learning systems that model adaptation or plasticity with a rich and realistic stream of information. Abstract Submission Deadline (extended): Sep 12, 2014, Article Submission Deadline: Jan 12, 2015 Topic Editor(s): Andrea Soltoggio, Frank van der Velde Frontiers, a Swiss open-access publisher, recently partnered with Nature Publishing Group to expand its researcher-driven Open Science platform. Frontiers articles are rigorously peer-reviewed, can be disseminated freely and are widely read by your colleagues and by the broader scientific and medical research communities. The idea behind a research topic is to create an organized, comprehensive collection of several contributions, as well as a forum for discussion and debate. Contributions can be articles describing original research, methods, hypothesis & theory, opinions, etc. We have created a homepage on the Frontiers website (Frontiers in Neurorobotics) where all articles will appear after peer-review and where participants in the topic will be able to hold relevant discussions: http://www.frontiersin.org/Neurorobotics/researchtopics/Neural_plasticity_f…. Frontiers will also compile an e-book, as soon as all contributing articles are published, that can be used in classes, be sent to foundations that fund your research, to journalists and press agencies, or to any number of other organizations. As such, a manuscript accepted for publication incurs a publishing fee, which varies depending on the article type. Research Topic manuscripts receive a significant discount on publishing fees. Please take a look at this fee table: http://www.frontiersin.org/about/PublishingFees. Once published, your articles will remain free to access for all readers, and will be indexed in PubMed and other academic archives. As an author in Frontiers, you retain the copyright to your own papers and figures. Should you choose to participate, please confirm by sending me a quick email and then your abstract no later than Sep 12, 2014 using the following link:http://www.frontiersin.org/Neurorobotics/researchtopics/Neural_plastic… With best regards, Frank van der Velde and Andrea Soltoggio Guest Associate Editors, Frontiers in Neurorobotics www.frontiersin.org

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Seeking community input for Neurodata Without Borders
by Jeff Teeters 13 Aug '14

13 Aug '14

Dear Colleague, The Neurodata Without Borders (NWB) project has just started. The project goal is to build a common data format for neurophysiology data from Allen Brain Institute, Janelia Farm and two labs from NYU and Caltech. Although focusing on a limited set of use cases, the project also aims to develop products that will serve the broader community. At this point we would like to solicit community input about ideas/approaches for designing a generalizable neurophysiology data format. If you are interested in contributing to this project, please review the project description at: https://crcns.org/NWB and fill out the questionnaire: https://docs.google.com/forms/d/1CNTd4M-8kQ_WhEZc7n7WxpTa0LOupt_q3z21E1fRxj… On the basis of the questionnaire responses and ensuing communication, we will organize the first hackathon meeting of the project, to be held November 20 – 22, 2014 (just after SfN) at Janelia Farm, in Ashburn, Virginia. At this hackathon we will discuss in detail the requirements for a common format based on the project use cases and also discuss, compare and evaluate alternative techniques for implementing the common format. More information about the project is available in a recent press release: http://www.kavlifoundation.org/kavli-news/prominent-us-research-institution… Please forward this email to anyone you know with relevant expertise who may be interested in contributing to this project. Thank you, Fritz Sommer and Jeff Teeters Redwood Center for Theoretical Neuroscience UC Berkeley

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DEADLINE EXTENDED: 8th International Conference on Bio-inspired Information and Communications Technologies (BICT 2014, formerly BIONETICS)
by Jun Suzuki 12 Aug '14

12 Aug '14

CFP: 8th International Conference on Bio-inspired Information and Communications Technologies (BICT 2014, formerly BIONETICS) http://www.bionetics.org/ Paper submission deadline extended: September 1, 2014 December 1 (Mon) - December 3, 2014 (Wed) Boston, MA, USA In-corporation with ACM BICT 2014 aims to provide a world-leading and multidisciplinary venue for researchers and practitioners in diverse disciplines that seek the understanding of key principles, processes and mechanisms in biological systems and leverage those understandings to develop novel information and communications technologies (ICT). BICT 2014 targets two thrusts: THRUST 1: Indirect/Weak Bioinspiration (ICT designed after biological principles, processes and mechanisms). Examples include evolutionary computation, artificial gene regulatory networks, neural computation, swarm intelligence, cellular automata, artificial immune systems, artificial life, artificial chemistry, reaction-diffusion computing, simulated annealing, self-organization and network science. THRUST 2: Direct/Strong Bioinspiration (ICT utilizing biological materials and systems). Examples include cellular computing, molecular computing/communication, membrane computing, DNA computing and memory, bacterial computing, Physarum computing and quantum computing. Expected, but not exclusive, topics are: * Signal/information processing and communication for bio-inspired ICT * Algorithms and their applications for bio-inspired ICT * Formal models and methods for bio-inspired ICT * Bio-inspired software and hardware systems * Modeling, simulations and empirical experiments of bio-inspired ICT * Self-* and stability properties in bio-inspired ICT * Security, robustness and resilience in bio-inspired ICT * Design, configuration and management issues in bio-inspired ICT * Software engineering and performance engineering in bio-inspired ICT * Tools, testbeds and deployment aspects in bio-inspired ICT * Applications, experiences and standardization of bio-inspired ICT * Socially-aware, game theoretic and other metaphor-assisted interdisciplinary research Application domains include, but not limited to, autonomic computing, bioinformatics, biomedical engineering, computer networks, computer vision, data mining, e-health, green computing and networking, grid/cloud computing, intelligent agents, mechanical engineering, molecular communication, nano-scale computing and networking, optimization, pervasive computing, robotics, security, social networks, software engineering and systems engineering. IMPORTANT DATES: Regular paper submission due: September 1 Short and poster/demo paper submission due: September 22 Notification for regular papers: September 22 Notification for short and poster/demo papers: October 6 Camera ready due: October 13 SPECIAL TRACKS: In addition to the regular track that covers general/mainstream topics, BICT 2014 features the following special tracks that focus on specific, emerging or underrepresented topics. * Artificial, Biological and Bio-Inspired Intelligence (ABBII) * Artificial Intelligence and Software Engineering (AISE) * Body Area Soft Computing (BASC) * Biologically-Inspired Process Calculi (BIPC) * Bio-Inspired Machine Vision (BIMV) * Bio-inspired/Biomimetic Microsystems & Microdevices (BMM) * Bio-inspired Wireless Network Security (BWNS) * Complex Adaptive Systems (CAS) * Engineering Applications from Molecular and Gene Regulatory Networks (EMNET) * Molecular Communication and Networking (MCN) * Morphogenetic Collective Systems (MCS) * Modularization for Practical Software Engineering (MPSE) * Resilient Networks (RN) * Swarm and Modular Robotics (SAMR) * Smart Body Area Networks (SBAN) * Security and Privacy in Bio-inspired Networks (SPBN) PAPER SUBMISSION: Authors are invited to submit regular papers (up to 8 pages each), short papers (up to 4 pages each) or poster/demo papers (up to 2 pages each) in ACM's paper template. Up to two extra pages are allowed for each paper with extra page charges. See http://bionetics.org/2014/show/initial-submission for more details. PUBLICATION: All accepted paper will be published through ACM Digital Library and submitted for indexing by SI, EI Compendex, Scopus, ACM Library, Google Scholar and many more. Selected papers will be considered for publication in leading journals including: * ACM/Springer Mobile Networks and Applications * Elsevier Information Sciences * Elsevier Nano Communication Networks Journal * Int'l Journal of Software Engineering and Knowledge Engineering * Cloud-integrated Cyber-Physical Systems (Springer book) KEYNOTE SPEAKERS: * Andrew Adamatzky, University of the West of England, Bristol, UK * Gabriel Ciobanu, Romanian Academy, ICS, Iasi, Romania * Andrew Eckford, York University, Canada * Valeriy Perminov, BioTeckFarm, Ltd., Russia * Hiroki Sayama, SUNY Binghamton, USA * Theresa Schubert, Bauhaus-Universität Weimar, Germany * Jon Timmis, University of York, UK * Honggang Wang, University of Massachusetts, Dartmouth, USA * Justin Werfel, Harvard University, USA GENERAL CHAIR: Jun Suzuki, University of Massachusetts, Boston, USA PC CHAIR: Tadashi Nakano, Osaka University, Japan PC VICE CHAIRS: Andrew Adamatzky, University of the West of England, UK Gabriel Ciobanu, Romanian Academy, Institute of Computer Science, Romania Douglas Dow, Wentworth Institute of Technology, USA Hiroaki Fukuda, Shibaura Institute of Technology, Japan Tyler Garaas, Mitsubishi Electric Research Laboratories, USA Preetam Ghosh, Virginia Commonwealth University, USA Isao Hayashi, Kansai University, Japan Yu-Hsiang Hsu, National Taiwan University, Taiwan Saori Iwanaga, Japan Coast Guard Academy, Japan Masao Kubo, National Defense Academy, Japan Paul Leger, Universidad Católica del Norte, Chile Shih-Hsi "Alex" Liu, California State University, Fresno, USA Michael L. Mayo, US Army Engineer Research and Development Center, USA Parisa Memarmoshrefi, University of Goettingen, Germany Marjan Mernik, University of Maribor, Slovenia Alan Millard, University of York, UK Michael Moore, USA Marc Pomplun, University of Massachusetts Boston, USA Florian Raudies, Boston University, USA Hiroshi Sato, National Defense Academy, Japan Hiroki Sayama, SUNY Binghamton, USA Tomohiro Shirakawa, National Defense Academy of Japan, Japan Jon Timmis, University of York, UK Athanasios Vasilakos, University of Western Macedonia, Greece Honggang Wang, University of Massachusetts Dartmouth, USA Jun Zhou, Shanghai Jiao Tong University, China

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Parallel computing workshop at SFN 2014 meeting
by Ted Carnevale 12 Aug '14

12 Aug '14

What: Using the Neuroscience Gateway Portal for Parallel Simulations A Satellite Symposium at the 2014 Society for Neuroscience Meeting Where: Location to be announced in downtown Washington, DC When: 9 AM - Noon on Saturday, November 15, 2014 Speakers to include: A. Majumdar, S. Sivagnanam, and T. Carnevale Registration deadline: Friday, October 31, 2014 This workshop is for neuroscientists who need to use parallel supercomputers for large modeling projects. With support from NSF, we have been developing the Neuroscience Gateway Portal (NSG) http://www.nsgportal.org/, which * provides free CPU time on NSF-supported high performance computing resources * has a browser-based interface that simplifies the tasks of uploading models, specifying job parameters, monitoring job status, and storing and retrieving output data * already has many widely-used simulatiors optimally installed and configured, including Brian, GENESIS3, NEST, NEURON, and PyNN The workshop will combine didactic presentations by NSG's developers, discussions with experienced users, and hands on instruction in how to use the portal. Come find out how the NSG can be useful in your own research! For more information and the online registration form see http://www.neuron.yale.edu/neuron/static/courses/nsg2014/nsg2014.html --Ted

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postdoctoral position, Deep Brain Stimulation in Parkinson's disease, IUPUI and Purdue University
by Leonid Rubchinsky 12 Aug '14

12 Aug '14

Postdoctoral opening in computational neuroscience The Department of Mathematical Sciences at Indiana University-Purdue University Indianapolis (IUPUI) invites applications for a postdoctoral position in the area of mathematical and computational neuroscience. The position is with a collaborative group of scholars from the Department of Mathematical Sciences at IUPUI, Weldon School of Biomedical Engineering at Purdue University and the Department of Neurosurgery of the Indiana University School of Medicine. The current research project is aimed at the development of adaptive deep brain stimulators for Parkinson's disease. Part of the duties may also include some teaching in the Mathematical Sciences. The position offers excellent interdisciplinary training possibilities in mathematical biology and computational neuroscience. Qualifications: Applicants are expected to have a Ph.D. in mathematics, physics, neuroscience, biomedical engineering, computer science or other related field. Applicants should have strong quantitative skills in data analysis and modeling and a strong interest in neuroscience applications. Experience in nonlinear dynamics/control theory/neurophysiology is a plus. How to apply: Send your CV with a list of publications, research statement, and arrange two-three recommendation letters to be sent to Dr. Leonid Rubchinsky via e-mail: leo(a)math.iupui.edu. Address all your inquiries to the same e-mail. Alternatively send your application by regular mail to: Dr. Leonid Rubchinsky, Department of Mathematical Sciences, IUPUI, 402 N. Blackford Street, LD 270, Indianapolis, IN 46202. Screening of applications will continue until position is filled. IUPUI is an EEO/AA Employer, M/F/D. *********************** Leonid Rubchinsky, PhD Associate Professor Department of Mathematical Sciences, Indiana University - Purdue University, Indianapolis Stark Neurosciences Research Institute, Indiana University School of Medicine 402 N. Blackford St Indianapolis, IN 46202 leo(a)math.iupui.edu http://www.math.iupui.edu/~leo 317-274-9745 317-274-3460 (fax) ***********************

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Job offer: PhD student position
by Seeger, Simone 12 Aug '14

12 Aug '14

The Department of Theoretical Neuroscience (Head: Prof. Daniel Durstewitz) at the Central Institute of Mental Health (Mannheim) invites applications for a PhD student position (E 13 TV-L) (50% of the fulltime weekly hours) in the newly founded research group Data-driven network models of higher cognitive functions (Head: Dr. Joachim Hass) to be filled as soon as possible. The position is initially limited for 3 years. The research group develops biologically realistic computational neural network models of the neocortical structures such as the prefrontal cortex and the motor cortex. These models closely adhere to physiological data from both in vitro and in vivo experiments and are used to study higher cognitive functions such as time perception and working memory. The successful candidate will work in the project "The human mirror neuron system - measurement and beyond" funded by the Heidelberg Academy for Sciences and Humanities. The joint project of the Departments of Theoretical Neuroscience and Clinical Psychology of the Central Institute of Mental Health aims at a deeper understanding of the mirror neuron system in humans, which is thought to play a crucial role in social cognition by representing the emotions and intentions of others in the motor cortex. The project combines multimodal measurements (involving fMRI, EEG, transcranial magnetic stimulation and genotyping) with computational modeling. The Central Institute of Mental Health is an internationally renowned research institute for psychiatry and neuroscience as well as a clinic for psychiatry, psychotherapy and psychosomatics (part of the medical faculty of the University of Heidelberg). The research group closely interacts with neurobiologists and psychologists at the institute. The Department of Theoretical Neuroscience is focused on computational modeling and statistical data analysis of prefrontal cortex and hippocampus functions. It is one of the core research units of the Bernstein Center for Computational Neuroscience (BCCN) Heidelberg-Mannheim. Access to high-performance computing facilities is provided. Tasks: The project involves the development of a rate-based, brain-scale model as well as the further development of an existing spiking network model of the motor cortex. The resulting twostage model is then being adapted to the multimodal experimental data using stochastic optimization techniques. In particular, the effects of the transcranial magnetic stimulation and different levels of dopamine and oxytocin are to be implemented in the model and directly compared with the experimental data. Participation in the project organization and publication writing is also expected. It is also possible to participate in the analysis of the fMRI data. Requirements: The candidate should have a university degree (master or equivalent) in physics, mathematics, computer science, computational neuroscience or similar, a strong interest in neurobiological research and very good programming skills (ideally in MATLAB and C). Good communication skills in English as well as knowledge in nonlinear dynamics, numerical optimization or neural modeling are also required. Knowledge in neuroscience or experimental psychology is beneficial. Applicants should sent their application documents (cover letter including a brief description of personal qualifications and future research interests, CV and contact details of two personal references) to joachim.hass(a)zi-mannheim.de<mailto:joachim.hass@zi-mannheim.de>. Questions and informal discussions about the position are also welcome under this email address. The call is open until the position is filled. *** Simone Seeger, M.A. Administration Bernstein Center for Computational Neuroscience Zentralinstitut für Seelische Gesundheit Postfach 12 21 20, 68072 Mannheim J5, 68159 Mannheim Telefon: 0621/1703-1326 oder 06221/54-8310 Fax: 0621/1703-2915 E-Mail: Simone.Seeger(a)zi-mannheim.de<mailto:Simone.Seeger@zi-mannheim.de> Internet: http://www.bccn-heidelberg-mannheim.de<http://www.bccn-heidelberg-mannheim.de/> *** Simone Seeger, M.A. Administration Bernstein Center for Computational Neuroscience Zentralinstitut für Seelische Gesundheit Postfach 12 21 20, 68072 Mannheim J5, 68159 Mannheim Telefon: 0621/1703-1326 oder 06221/54-8310 Fax: 0621/1703-2915 E-Mail: Simone.Seeger(a)zi-mannheim.de<mailto:Simone.Seeger@zi-mannheim.de> Internet: http://www.bccn-heidelberg-mannheim.de<http://www.bccn-heidelberg-mannheim.de/>

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Call for Papers: IEEE Computational Intelligence Magazine (CIM) Special Issue: "Computational Intelligence for Changing Environments"
by Dr Amir Hussain 11 Aug '14

11 Aug '14

Call for Papers (Please also forward to any interested colleagues - with advance apologies for any cross-postings!) IEEE Computational Intelligence Magazine (CIM) (http://cis.ieee.org/ieee-computational-intelligence-magazine.html) Special Issue on "Computational Intelligence for Changing Environments" (Submission Deadline: 15 Nov 2014) (http://www.cs.stir.ac.uk/~ahu/IEEE-CIM-CICE2015.pdf) Guest Editors: Amir Hussain, Dacheng Tao, Jonathan Wu and Dongbin Zhao Aims and Scope: Over the past decade or so, computational intelligence techniques have been highly successful for solving big data challenges in changing environments. In particular, there has been growing interest in so called biologically inspired learning (BIL), which refers to a wide range of learning techniques, motivated by biology, that try to mimic specific biological functions or behaviors. Examples include the hierarchy of the brain neocortex and neural circuits, which have resulted in biologically-inspired features for encoding, deep neural networks for classification, and spiking neural networks for general modelling. To ensure these models are generalizable to unseen data, it is common to assume that the training and test data are independently sampled from an identical distribution, known as the sample i.i.d. assumption. In dynamic and non-stationary environments, the distribution of data changes over time, resulting in the phenomenon of ‘concept drift’ (also known as population drift or concept shift), which is a generalization of covariance shift in statistics. Over the last five years, transfer learning and multitask learning have been used to tackle this problem. Fundamental analyses using probably approximately correct (PAC) and Rademacher complexity frameworks have explained why appropriate incorporation of context and concept drift can improve generalizability in changing environments. It is possible to use human-level processing power to tackle concept drift in changing environments. Concept drift is a real-world problem, usually associated with online and concept learning, where the relationships between input data and target variables dynamically change over time. Traditional learning schemes do not adequately address this issue, either because they are offline or because they avoid dynamic learning. However, BIL seems to possess properties that would be helpful for solving concept drift problems in changing environments. Intuitively, the human capacity to deal with concept drift is innate to cognitive processes, and the learning problems susceptible to concept drift seem to share some of the dynamic demands placed on plastic neural areas in the brain. Using improved biological models in neural networks can provide insight into cognitive computational phenomena. However, a main outstanding issue in using computational intelligence for changing environments and domain adaptation is how to build complex networks, or how networks should be connected to the features, samples, and distribution drifts. Manual design and building of these networks are beyond current human capabilities. Recently, computational intelligence methods has been used to address concept drift in changing environments, with promising results. A Hebbian learning model has been used to handle random, as well as correlated, concept drift. Neural networks have been used for concept drift detection, and the influence of latent variables on concept drift in a neural network has been studied. In another study, a timing-dependent synapse model has been applied to concept drift. These works mainly apply biologically-plausible computational models to concept drift problems. Although these results are still in their infancy, they open up new possibilities to achieve brain-like intelligence for solving concept drift problems in changing environments. Taking the current state of research in computational intelligence for changing environments into account, the objective of this special issue is to collate this research to help unify the concepts and terminology of computational intelligence in changing environments, and to survey state-of-the-art computational intelligence methodologies and the key techniques investigated to date. Therefore, this special issue invites submissions on the most recent developments in computational intelligence for changing environments algorithms and architectures, theoretical foundations, and representations, & their application to real world problems. We also welcome timely surveys & review papers. Topics of Interest include (but are not limited to): • Computational intelligence methodologies and implementation for changing environments • Transfer learning, Multitask learning, Domain adaption • Incremental Learning architectures, Unsupervised and semi-supervised learning architectures • Incremental Knowledge augmentation, Representation learning and disentangling • Incremental Adaptive Neuro-fuzzy systems • Incremental and single-pass data mining • Incremental Neural Clustering & Regression • Incremental Adaptive decision systems • Incremental Feature selection and reduction • Incremental Constructive Learning • Novelty detection in Incremental learning Submission Process The maximum length for the manuscript is typically 25 pages in single column format with double-spacing, including figures and references. Authors should specify in the first page of their manuscripts the corresponding author’s contact and up to 5 keywords. Submission should be made via: https://easychair.org/conferences/?conf=ieee-cim-cice2015 Important Dates (for August 2015 Issue) 15th November, 2014: Submission of Manuscripts 15th January, 2015: Notification of Review Results 15th February, 2015: Submission of Revised Manuscripts 15th March, 2015: Submission of Final Manuscripts Guest Editors Professor Amir Hussain, University of Stirling, Stirling FK9 4LA, Scotland UK Email: ahu(a)cs.stir.ac.uk http://cs.stir.ac.uk/~ahu/ Professor Dacheng Tao, University of Technology, Sydney, 235 Jones Street, Ultimo, NSW 2007, Australia Email: dacheng.tao(a)uts.edu.au Professor Jonathan Wu University of Windsor 401 Sunset Avenue, Windsor, ON, Canada Email: jwu(a)uwindsor.ca Professor Dongbin Zhao Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China E-mail: dongbin.zhao(a)gmail.com -- The University of Stirling has been ranked in the top 12 of UK universities for graduate employment*. 94% of our 2012 graduates were in work and/or further study within six months of graduation. *The Telegraph The University of Stirling is a charity registered in Scotland, number SC 011159.

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FW: PhD/Researcher positions in Electrical Engineering, Computer Science or Biomedical Engineering
by Morgado Dias 09 Aug '14

09 Aug '14

Dear Members, Positions 3 and 4 might be interesting for the community. Best regards, Morgado ------------------------------------------------------ PhD/Researcher positions in Electrical Engineering, Computer Science or Biomedical Engineering The research group of Prof. Morgado Dias (Madeira Interactive Technologies Institute - Partner of the Carnegie Mellon University - Portugal program) is looking for PhD students and researchers for: (1) Monitoring and Fault detection in Photovoltaic parks (funded project-1year-possible follow-up with a PhD) (2) 3D Image Processing (funded project-1year- possible follow-up with a PhD) (3) Hardware for Artificial Neural Networks, with emphasis on emerging architectures (PhD, but needs to be externally funded) (4) FPGA prototype for detecting sleep APNEA disorders (PhD – needs to apply to a specific program in Portugal for funding if required) Information about the Institute, University and Region: Madeira Interactive Technologies Institute - Partner of the Carnegie Mellon University - Portugal program, is an innovation institute established as an associated independent non-profit R&D organization whose founding members are the University of Madeira, Madeira Tecnopolo S. A. and Carnegie Mellon University. Recently awarded a 2,4M€ funding, Madeira-ITI operates in the interdisciplinary domain of human-computer interaction encapsulating contributions from computer science, psychology and design in order to address/engage in important scientific and technological challenges that are both relevant to society and have significant economic impact (www.m-iti.org <http://www.m-iti.org> ). The University of Madeira is an active public university integrated in Portuguese Higher Education System and the European Community. Madeira is a small island with paradisiac living conditions and warm people. Recently elected as the Best European Island, you will find in a small place a diversity of landscapes that go from the beach to the mountain with low living costs and almost no crime. Prof. Morgado Dias research expertise includes Artificial Neural Networks, FPGAs and Renewable Energy. More information can be found at: http://www.cee.uma.pt/morgado/ Profile for candidates: (1) A master’s degree in Electrical Engineering, Computer Science, Biomedical Engineering or Computer Engineering (preferred) or an undergraduate degree in the same areas, completed before arrival. (2) Good oral and spoken English as well as good communication skills. TOEFL or IELTS scores are encouraged. At least the English proficiency that fulfills the requirements of CSC applications is necessary. (3) Teamwork spirit. (4) Self-motivation and independent working ability. (5) Knowledge of and research experience related to the above fields are strongly preferred. (6) Previous published work and interest in pursuing a PhD is preferred. Application: If you are interested, please address your motivation letter (with a brief description of yourself, research ability & interest) and CV to: morgadoatuma.pt <mailto:morgado@uma.pt> --- Este email está livre de vírus e malware porque a proteção avast! Antivirus está ativa. http://www.avast.com

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PhD opportunities at the Queensland Brain Institute
by Geoffrey Goodhill 08 Aug '14

08 Aug '14

PhD Positions at the Queensland Brain Institute (QBI), The University of Queensland Application deadline Oct 1st 2014 The Queensland Brain Institute (www.qbi.uq.edu.au) is seeking exceptional and highly motivated PhD candidates to undertake neuroscience research at its state-of-the-art building located at The University of Queensland’s (UQ) St Lucia campus, Brisbane, Australia. UQ has 45,000 students (12,000 postgraduate) and is ranked in the top 100 universities in the world. QBI is one of UQ’s flagship research institutes, with researchers working to understand the fundamental mechanisms of brain function, and applying such research to the development of new therapeutics to combat diseases where brain function is compromised. The Institute’s multidisciplinary environment is home to more than 400 staff and students. Key areas of interest include: • Ageing Dementia and Alzheimer’s Disease • Cognition and Behaviour • Computation and Neuronal Circuits • Neurogenesis and Neuronal Survival • Genetics and Epigenetics • Neuronal Development and Connectivity • Sensory Systems • Synaptic Function Since establishment in 2003 QBI researchers have published >1200 papers in the world’s foremost journals, including 460 in the past 2 years. QBI is 100 metres from UQ's Centre for Advanced imaging (www.cai.uq.edu.au) which houses 7T human and 16.4T animal MRI scanners. Scholarships and Remuneration QBI offers full-time PhD scholarships for outstanding Australian and International students (living allowance AU$25,392 per annum, indexed annually, tax exempt) for 3 years with a possible 6 month extension. In addition, QBI supports high quality domestic and international applicants in their nomination to The University of Queensland’s competitive scholarship rounds (three rounds per year). A QBI top-up scholarship of $5,000 per annum may also be available to successful candidates. Candidates should have a First Class Honours degree (or equivalent) in neuroscience, molecular biology, bioscience, psychology, genetics, physical sciences, engineering, mathematics or a related discipline. Strong academic performance, the commitment to conduct high quality neuroscience research, and published output are highly desirable. For further information on the Basis of Admission to a UQ research higher degree, please visit http://www.uq.edu.au/grad-school/our-research-degrees. Successful applicants must accept and commence within 6 months of receiving an award. Enquiries and Applications Please review the research interests of QBI Group Leaders at http://www.qbi.uq.edu.au/group-leaders and make direct contact with a Group Leader working in an area of greatest interest to you, providing your detailed academic resume and complete academic records (including GPA scores/grades, and grading scale details). The Group Leader will work with you to develop your application for submission to QBI. Applications close on 1 October, 2014 Professor Geoffrey J Goodhill Queensland Brain Institute and School of Mathematics & Physics University of Queensland St Lucia, QLD 4072, Australia Email: g.goodhill(a)uq.edu.au http://www.qbi.uq.edu.au/professor-geoffrey-goodhill

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