A funded PhD position is available at the University of Edinburgh to develop and implement efficient paralellised methods for analysis of large scale, high density multielectrode array recordings. The project will focus on analysis of primary raw data from a 4,096 channel array, and aims at improving spike detection and sorting, and statistical analysis of multi-neuron activity. Data will come from the labs of Evelyne Sernagor (Newcastle, retina) and Luca Berdondini (IIT Genova, cultured networks). Applicants should have a strong quantitative background and interest in interdisciplinary research. Background in neuroscience and/or parallel programming is desirable, but not essential. This position is available to UK/EU applicants, and eligible for funding by the EPSRC CDT in Pervasive Parallelism. Interested individuals should send a c.v., statement of interest and the names of three references to Matthias Hennig (h.hennig@ed.ac.uk). Apply by 1 February 2016. PPar http://pervasiveparallelism.inf.ed.ac.uk/ J.-O. Muthmann, H. Amin, E. Sernagor, A. Maccione, D. Panas, L. Berdondini, U.S. Bhalla, M.H. Hennig (2015). Spike detection for large neural populations using high density multielectrode arrays. Front Neuroinform, 9:28. http://journal.frontiersin.org/article/10.3389/fninf.2015.00028/abstract D. Panas, H. Amin, A. Maccione, O. Muthmann, M. van Rossum, L. Berdondini, M.H. Hennig (2015). Sloppiness in spontaneously active neuronal networks. J Neurosci, 35(22): 8480-8492. http://www.jneurosci.org/content/35/22/8480.full -- Matthias H Hennig http://homepages.inf.ed.ac.uk/mhennig/ -- Matthias H Hennig http://homepages.inf.ed.ac.uk/mhennig/ The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336.
participants (1)
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Matthias Hennig