Fast Analog Computing with Emergent Transient Stat.. (FACETS-ITN)
Fast Analog Computing with Emergent Transient States - Initial Training Network (FACETS-ITN)
Start date: Sep 1, 2009,
End date: Aug 31, 2013
FACETS-ITN is a research and training network involving partners from 11 universities and research centres, 3 industrial companies and 1 semi-industrial research centre from 6 European countries. It combines competencies in neurobiology, computational neuroscience, information science, physics and electrical engineering. The scientific goal is to experimentally and theoretically explore the structure and the computational principles of biological neural circuits using in-vitro and in-vivo neurobiological experiments as well as analytical approaches, model building and simulation techniques. The concepts of learning and plasticity will be of particular importance. Based on the input from biology and modelling it is expected to prepare the grounds for novel hardware based computing devices that make use of such principles. Such devices will be built and operated in the form of large scale demonstrators as part of the research plan. Within the training network 21 selected Ph.D. students will be integrated into an existing international research environment and receive a strongly interdisciplinary training. The training comprises an intense exchange and visiting programme, specific training workshops for all scientific areas covered as well as in non-scientific key competencies.. This training concept will enhance their original academic education in order to cope with the challenges of this diverse international research environment. The proposed training programme will be closely coupled to existing research projects as well as graduate programmes of participating universities. It will create a sustained infrastructure based on web-based learning as well as on scientific interdisciplinary networks and the intersectional exchange with industry. The community building among Ph.D. students from different disciplines will include students from other projects, in particular the current FACETS integrated project and its planned successor.
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