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Fully funded postdoctoral position in Machine Learning and Computational Biology at Royal Holloway University of London

by Alberto Paccanaro

[Apologies for cross-posting] Application deadline: 10th April 2016 ==================================================== Applications are invited for a postdoctoral position at the Department of Computer Science of Royal Holloway, University of London. The successful candidate will work with Prof Alberto Paccanaro on different projects in the area of Systems Biology and Network Medicine -- please see http://www.paccanarolab.org/ for a description of the research carried out in the lab. Candidates should have a PhD degree in a relevant quantitative field (e.g. Computer Science, Statistics, Engineering), a strong background in machine learning and a keen interest in computational biology. Previous experience in the area of graphical models would be an asset for this position. The successful candidate will have the opportunity to collaborate with members of the interdisciplinary Centre for Systems and Synthetic Biology (Computer Science and Biological Sciences) at Royal Holloway and collaborators at Imperial College, University of Tennessee and Yale University. The post is therefore ideal for someone with a computer science or maths background who is looking to move into computational biology. This post is based in the Department of Computer Science in Egham, Surrey where the College is situated in a beautiful, leafy campus near to Windsor Great Park and within commuting distance from London (see http://www.royalholloway.ac.uk/) This is a full time post, available immediately, or as soon as possible thereafter for a fixed term period of 30 months. The salary is in the range £33,789 to £39,902 per annum inclusive of London Allowance. The position is funded by a joint BBSRC/NSF grant. To apply go to: https://jobs.royalholloway.ac.uk/vacancy.aspx?ref=0316-094 For an informal discussion about the post, please contact Prof Alberto Paccanaro, alberto(a)cs.rhul.ac.uk. The Human Resources Department can be contacted with queries by email at: recruitment(a)rhul.ac.uk. Please quote the reference: 0316-094. Closing Date: Midnight, 10th April 2016. Interview Date: To be confirmed. The College is committed to equality and diversity, and encourages applications from all sections of the community. -- ===================================== Prof. Alberto Paccanaro Department of Computer Science Royal Holloway, University of London Phone: +44 1784 414239 Homepage: http://www.cs.rhul.ac.uk/home/alberto/ Lab page: http://www.paccanarolab.org

March 15, 2016

ICLR 2016 Registration Open

by Hugo Larochelle

4th International Conference on Learning Representations (ICLR 2016) Website: http://www.iclr.cc/ Location: Caribe Hilton, San Juan, Puerto Rico, May 2-4, 2016 Registration to ICLR 2016 is now open: http://www.iclr.cc/doku.php?id=iclr2016:registration The lower early registration fees and hotel rates are available until April 1st. For more information on ICLR 2016, please visit http://www.iclr.cc/doku.php?id=iclr2016:main. We look forward to seeing you in Puerto Rico! Yoshua Bengio, Université de Montreal, General Chair Yann LeCun, New York University and Facebook, General Chair Hugo Larochelle, Twitter and Université de Sherbrooke, Senior Program Chair Brian Kingsbury, IBM Watson Group, Program Chair Samy Bengio, Google, Program Chair

March 15, 2016

Funded vision science PhD opportunities at Royal Holloway, University of London

by Durant, Szonya

Please see opportunities below to work with me (Szonya Durant) as supervisor and Angelika Lingnau or Jonas Larsson in the Department of Psychology at Royal Holloway, University of London. There are two main proposed areas: Investigating the neural representation of action recognition categories What are the neural sources and function of expectation signals in human visual processing? Both projects involve EEG and fMRI methods, but experience is not essential and training will be provided as part of the PhD. Please email szonya.durant(a)rhul.ac.uk<mailto:szonya.durant@rhul.ac.uk> for more detail on these projects and the application process. Strong students from Psychology/Neuroscience/Cognitive Science/Computer Science/Biological Science/Physics/Mathematics are encouraged to apply. Suitable candidates (in collaboration with the supervisor) will need to develop a PhD proposal, which the department will use to evaluate applications - the department deadline for proposals is the 15th of April (so please get in touch asap). There are 4 paid studentships available in the department for UK and EU students. ********************************************************************** Szonya Durant Department of Psychology Royal Holloway, University of London Egham TW20 0EX 01784 276522

March 15, 2016

A new julia package for modelling spiking neural network

by Yao Lu

SpikingNetworks.jl <https://github.com/YaoLuCNS/SpikingNetworks.jl> is a julia package for computational neuroscientists to simulate large scale spiking neural network. It is inspired by Brain2 <http://briansimulator.org/>, and achieve most of the functionalities in Brian2 with faster speed, cleaner syntax and flexibility. Julia <http://julialang.org/> is a technical computing language, which relies on LLVM to achieve efficiency comparable to C. Julia has MATLAB-like syntax and is user-friendly to MATLAB users. This this package aims at experienced computational neuroscientists who want faster speed. Yao Lu

March 15, 2016

PhD studentships at Keele University - Closing Date: 15 April 2016

by Peter Andras

*Fully Funded Computer Science PhD Studentships at Keele University* The Faculty of Natural Sciences at Keele University is pleased to announce up to 7 fully-funded PhD studentships for UK/EU students for start in September/October 2016, as well as opportunities for part-funded PhD studentships for suitable candidates. Applications are invited from high quality prospective doctoral candidates in Computer Science and other disciplines. We welcome candidates with a good fit to our research specialisms and the expertise of our academic staff. Candidates are expected to have a 1st class or 2.1 class undergraduate degree or a Distinction level MSc degree in a relevant subject (or equivalent in the case of candidates from other EU countries). One of our focus areas in Computer Science is *Computational Neuroscience and Biomedical Engineering*. A selection of topics of interests in this area is provided below. *Computational Neuroscience and Biomedical Engineering*: computational modelling of the stomatogastric nervous system; bio-inspired robot control; computational modelling of cognitive behaviour in bees; neuro-control of evolving artificial creatures; neuro-control of robotic swarms; computational analysis of neuroimaging and multi-electrode array data; human and animal behaviour analysis using accelerometer data; virtual reality and robotics for rehabilitation engineering; analysis and modelling of the impact of neuromodulators in biological neural systems; big data analytics and neuro-degenerative disorders. *Funding* Each fully-funded studentship includes an annual tax-free stipend at RCUK rate plus tuition fees (currently £14,296 for stipend and £4,121 for fees). The funding is available for 3 years. Each studentship has an associated research expense budget (£2,000 – £3,000 per year, depending on the nature of the project, to cover project related consumables and conference travel). Opportunities are also available for candidates from the UK/EU and overseas who can demonstrate that they can fully or partially self-fund. If you are interested in this route, please contact Professor Peter Andras at p.andras(a)keele.ac.uk for a discussion. *Closing Date* The *closing date* for applications is Friday *15 April 2016* Full details and application procedures can be found on the website: http://www.keele.ac.uk/pgresearch/howtoapply/ For the purpose of research proposal applicants should submit an outline of their research interests or of a particular research project that the applicant would like to work on (max. 2 pages). Please send any questions by email to Lisa Cartlidge ( l.j.cartlidge(a)keele.ac.uk) or Ann Billington (a.billington(a)keele.ac.uk)

March 14, 2016

Postdoctoral Position in Computational Neuroscience/Biophysical Modeling

by Gabbiani, Fabrizio

Postdoctoral Position in Computational Neuroscience/Biophysical Modeling Computational and Applied Mathematics Rice University and Department of Neuroscience Baylor College of Medicine Houston, Texas ----- A postdoctoral position in computational neuroscience is available at Rice University and Baylor College of Medicine, in the laboratories of Steven Cox (Rice University) and Fabrizio Gabbiani (Baylor College of Medicine). Our research focuses on understanding the biophysical mechanisms underlying the implementation of non-linear operations by neurons and neuronal circuits. The postdoctoral research associate will model the cellular and network mechanisms underlying collision avoidance behaviors using advanced mathematical techniques and computer simulations. Modeling will be supported by a large data set of experimental data gathered using electrophysiology, pharmacology, calcium imaging, high-speed video imaging and telemetry. We are looking for a highly motivated candidate with a strong background in computational modeling of single neurons and neuronal circuits. Experience with Matlab and NEURON is required. The position is available for one year, with possibility of renewal for a second year, contingent of performance and funding availability. Salary will be commensurate with level of experience, based on an NIH scale. Applications will be accepted until April 15, 2016. Our labs are located at Rice University and in the adjacent Texas Medical Center, close to many of Houston's cultural and outdoor amenities. For further information about Rice University, the Texas Medical Center and Houston please visit http://www.explore.rice.edu/explore/General_Information.asp or https://www.bcm.edu/about-us/life-in-houston For further informal inquiries and to apply, please send CV, the names and full contact information of two to three references, as well as one to two representative publications to cox(a)rice.edu and gabbiani(a)bcm.edu. Equal Opportunity Employer: Females / Minorities / Veterans/ Disabled / Sexual Orientation / Gender Identity.

March 14, 2016

Eleventh Advanced Statistics and Data Mining Summer School (Madrid, June 27th - July 8th, 2016)

by asdm＠fi.upm.es

Dear colleagues, The Technical University of Madrid (UPM) will once more organize the 'Madrid UPM Advanced Statistics and Data Mining' summer school. The summer school will be held in Boadilla del Monte, near Madrid, from June 27th to July 8th. This year's edition comprises 12 week-long courses (15 lecture hours each), given during two weeks (six courses each week). Attendees may register in each course independently. No restrictions, besides those imposed by timetables, apply on the number or choice of courses. Early registration is now *OPEN*. Extended information on course programmes, price, venue, accommodation and transport is available at the school's website: http://www.dia.fi.upm.es/ASDM There is a 25% discount for members of Spanish AEPIA and SEIO societies. Please, forward this information to your colleagues, students, and whoever you think may find it interesting. Best regards, Pedro Larranaga, Concha Bielza, Bojan Mihaljevic and Laura Anton-Sanchez. -- School coordinators. *** List of courses and brief description *** * Week 1 (June 27th - July 1st, 2016) * 1st session: 9:45-12:45 Course 1: Bayesian Networks (15 h) Basics of Bayesian networks. Inference in Bayesian networks. Learning Bayesian networks from data. Real applications. Practical demonstration: GeNIe, Weka, Bayesia, R. Course 2: Time Series(15 h) Basic concepts in time series. Descriptive methods for time series. Linear models for time series. Extensions. Practical demonstration: R. 2nd session: 13:45-16:45 Course 3: Supervised Pattern Recognition (15 h) Introduction. Assessing the performance of supervised classification algorithms. Preprocessing. Classification techniques. Combining multiple classifiers. Comparing supervised classification algorithms. Practical demonstration: Weka. Course 4: Bayesian Inference (15 h) Introduction: Bayesian basics. Conjugate models. MCMC and other simulation methods. Regression and Hierarchical models. Model selection. Practical demonstration: R and WinBugs. 3rd session: 17:00 - 20:00 Course 5: Neural Networks and Deep Learning (15 h) Introduction. Training algorithms. Learning and Optimization. MLPs in practice. Deep Networks. Course 6: Unsupervised Pattern Recognition (15 h) Introduction to clustering. Data exploration and preparation. Prototype-based clustering. Density-based clustering. Graph-based clustering. Cluster evaluation. Miscellanea. Conclusions and final advise. Practical session: R. * Week 2 (July 4th - July 8th, 2016) * 1st session: 9:45-12:45 Course 7: Statistical Inference (15 h) Introduction. Some basic statistical test. Multiple testing. Introduction to bootstrap methods. Introduction to Robust Statistics. Practical demonstration: R. Course 8: Big Data with Apache Spark (15 h) Introduction. Spark framework and APIs. Data processing with Spark. Spark streaming. Machine learning with Spark MLlib. 2nd session: 13:45-16:45 Course 9: Text Mining (15 h) Introduction. Language Modeling. Text Similarity. Text Classification. Information Extraction. Practical session: Python, with Jupyter notebooks. Course 10: Feature Subset Selection (15 h) Introduction. Filter approaches. Embedded methods. Wrapper methods. Advanced topics. Practical session: R and Weka. 3rd session: 17:00-20:00 Course 11: Support Vector Machines and Regularized Learning (15 h) Introduction. SVM models. SVM learning algorithms. Convex non differentiable optimization. Course 12: Hidden Markov Models (15 h) Introduction. Discrete Hidden Markov Models. Basic algorithms for Hidden Markov Models. Semicontinuous Hidden Markov Models. Continuous Hidden Markov Models. Unit selection and clustering. Speaker and Environment Adaptation for HMMs. Other applications of HMMs. Practical session: HTK.

March 14, 2016

Reminder: Deadline is tomorrow (March 15) for Fellowships for IBBM Course in Park City, Utah

by Rob MacLeod

Dear Colleagues, Just a quick reminder that tomorrow is the deadline for all submissions for fellowships to the Image Based Biomedical Modeling (IBBM) Summer Course in July, 2016. We encourage you to forward this email to your group and your community. If you have any question please let me know. Fellowship Application Deadline : March 15, 2016 Early Bird Registration Deadline: May 15, 2016 Registration Deadline: June 10, 2016 We look forward to welcoming you to Utah this summer. Best, The IBBM Team Park City Summer Course in Image Based Biomedical Modeling July 11-21, 2016 Newpark Resort in Park City, Utah ibbm.sci.utah.edu <http://ibbm.sci.utah.edu/> Contact: ibbm(a)sci.utah.edu <mailto:ibbm@sci.utah.edu> For Graduate Students, Postdocs, Faculty, and Industry. We invite students underrepresented in health-related sciences to apply. This course creates field-specific expertise and hands-on experience in bioelectric or biomechanical problems that arise in current biomedical research and clinical practice. It provides training in numerical methods, image analysis, and computational tools necessary to carry out end-to-end, image-based, subject-specific simulations in bioelectricity or biomechanics, using freely available software. Organizers: Rob Macleod, Jeff Weiss, and Ross Whitaker Supported by the National Institutes of Health (NIH), National Institute of General Medical Sciences (NIGMS)

March 14, 2016

CIBB2016 - Computational Intelligence methods for Bioinformatics and Biostatistics

by Andrea Bracciali

[Apologies for cross-postings] ======================================================================= CALL FOR PAPERS and SPECIAL SESSIONS ======================================================================= ======================================================================= CIBB 2016 13th International Meeting on Computational Intelligence methods for Bioinformatics and Biostatistics University of Stirling, Stirling, Scotland UK September 1-3 2016 http://www.cs.stir.ac.uk/events/cibb2016/ cibb2016(a)gmail.com ======================================================================= Scope The main goal of this 13th edition of the CIBB international conference is to provide a multi-disciplinary forum open to researchers interested in the application of computational intelligence, in a broad sense, to open problems in bioinformatics, biostatistics, systems and synthetic biology and medical informatics. Cutting edge methodologies capable of accelerating life science discoveries will be discussed. Following its tradition and roots, this year's meeting will bring together researchers from the international scientific community interested in advancements and future perspectives in bioinformatics and biostatistics. Also, looking at current trends and future opportunities at the edge of computer and life sciences, the application of computational intelligence to system and synthetic biology, and the consequent impact on innovative medicine will be of great for the conference. Theoretical and experimental biologists are also invited to participate in order to present novel challenges and foster multidisciplinary collaboration. The scientific program of CIBB 2016 will include Keynote Speakers, tutorials and special sessions. Contributed papers will be presented in plenary oral sessions, special sessions, or poster sessions. Topics of interest include, but are not restricted to: · Next generation sequencing bioalgorithms · Multi-omics data analysis · High dimensional statistical analysis of omics data · Algorithms for alternative splicing analysis · Algorithms for molecular evolution and phylogenetic analysis · Methods for the visualization of high dimensional complex omic data · Software tools for bioinformatics · Methods for comparative genomics · Methods for functional classification of genes · Methods for unsupervised analysis, validation and visualization of structures discovered in bio-molecular data · Health-Informatics and Medical Informatics. · Methods for the integration of clinical and genetic data · Heterogeneous data integration and data fusion for diagnostics · Algorithms for pharmacogenomics · Biomedical text mining and imaging · Methods for diagnosis and prognosis within personalized medicine · Statistical methods for the analysis of clinical data · Prediction of secondary and tertiary protein structures · Mass spectrometry data analysis in proteomics · Algorithms for molecular evolution and phylogenetic analysis · Bio-molecular databases and data mining · Mathematical modeling and automated reasoning on biological and synthetic systems · Computational simulation of biological systems · Methods and advances in systems biology · Spatio-temporal analysis of synthetic and biological systems · Network systems biology · Models for cell populations and tissues · Methods for the engineering of synthetic components · Modelling and engineering of interacting synthetic and biological systems · Software tools for bioinformatics, biostatistics, systems and synthetic biology Publication Accepted papers will be presented at the conference (at least one author is expected to register), and will be published on proceedings for conference distribution. Extended and revised versions of the papers presented at CIBB 2016 will be invited for a post-conference monograph. This is traditionally published in the Springer series of Lecture Notes in Bioinformatics (LNBI), (arrangements undergoing). Continuing the tradition of CIBB, we are planning to publish best papers in one (or more, as appropriate) special issue of an international scientific journal (such as BMC Bioinformatics, in the latest editions). Paper Submission Papers must be prepared following the guidelines illustrated on the CIBB web site and should be long between 4 and 6 pages. Papers should be submitted in PDF format on the Easy Chair conference system (link available on the web site). Tutorials and Special Sessions CIBB 2016 will run a number of Tutorials and Special Sessions. Any topic of interest for the conference is eligible for a tutorial. Tutorials typically last from one to three hours. Special sessions focus on a specific, possibly cutting-edge, topic of interest for CIBB 2016. Special session organisers will be responsible for call dissemination, reviewing process and organizing oral presentations. Typically, a special session will have at least 4 accepted papers and may have an invited speaker (to be negotiated). Tutorial proposals including title, one page long abstract, and short CV of presenters, are due by 15th March 2014. Please send proposals to cibb2016(a)gmail.com. Special Session proposals including the session's title and scope, short CV of sessions chairs, preliminary list of at least 4 potential authors are due by 15th March 2014. Proposals of special sessions will be evaluated as soon as they are submitted. A special session must have at least 4 accepted papers. Please send proposals to cibb2016(a)gmail.com Important Dates Tutorial and Special Session proposal: 25th March 2016 Paper submission deadline: 15th May 2016 Notification of acceptance: 22nd June 2016 Final paper due: 8th July 2016 Conference: 1st -3rd September 2016 General Chairs Andrea Bracciali, University of Stirling, UK David Gilbert, Brunel University London, UK Gilbert MacKenzie, UL, ENSAI and Keele, UK Biostatistics Technical Chair Marco Bonetti, Università Bocconi, Italy Bioinformatics Technical Chair Ivan Merelli, ITB-CNR, Italy Local Organizing Committee Chairs Leslie Smith, University of Stirling, UK Giulio Caravagna, Edinburgh University, UK Publicity Chair Francesco Masulli, University of Genoa, Italy Special Session and Tutorial Chair Claudia Angelini, IAC-CNR, Italy Publication Chair Riccardo Rizzo, ICAR-CNR, Italy Steering Commitee Pierre Baldi, University of California, Irvine, CA, USA Elia Biganzoli, University of Milan, Italy Clelia Di Serio, Vita-Salute San Raffaele University, Italy Alexandru Floares, Oncological Institute Cluj-Napoca, Romania Jon Garibaldi, University of Nottingham, United Kingdom Nikola Kasabov, Auckland University of Technology, New Zealand Francesco Masulli, University of Genova, Italy and Temple University, PA, USA Leif Peterson, TMHRI, Houston, Texas, USA Roberto Tagliaferri, University of Salerno, Italy

March 14, 2016

PhD student position available at Newcastle University

by Roman Bauer

Dear all, I invite applications for a fully-funded three-year PhD student position at the Institute of Neuroscience at Newcastle University, Newcastle upon Tyne (UK). The successful candidate will work under the supervision of Dr Roman Bauer and Dr Evelyne Sernagor, and do computational modeling as well as wet-lab work on neuronal development in the retina. There is also the possibility for the student to be involved in a collaborative project with CERN openlab and Intel as a project partner. Applicants should be highly motivated and should have a strong background in physics, computer science, neuroscience or a related disciplince. Good computational skills and experience in a major programing language such as C++ or Java are required. The Institute of Neuroscience (IoN) is a well-established research institute integrating over 75 principal investigators, and was ranked in UK top 10 for overall quality of research. The university's Faculty of Medical Sciences, of which IoN is part of, is ranked in the top 50 worldwide for biomedical and health sciences in the Leiden Ranking. More details on this job posting can be found here: http://www.ncl.ac.uk/postgraduate/funding/sources/allstudents/12mrea.html Best regards, Roman Bauer

March 14, 2016