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must either have a PhD in a relevant biological subject or have submitted or about to submit their PhD thesis. Candidates must also have demonstrable expertise in biochemistry, cell biology and/or
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the successful software package VASP (Vienna ab-initio Simulation Package). Currently, the group consists of two full professors, one associate professor, several postdocs and about 10 PhD and master students
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students and PhD students. Applicants will have, or be close to completing a PhD in a relevant field and possess relevant experience, in the area of probability or statistical machine learning. They will
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, state-of-the-art laboratories, high-performance computing, and industry collaboration through the London Institute for Healthcare Engineering. About the role We are looking for a highly motivated
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collaborative and interdisciplinary and the ability to work in a team is essential. About You The successful candidate will be expected to have a PhD degree in biological or computational sciences or equivalent
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with an international reputation for excellence. The Department has a substantial research programme, with major funding from Medical Research Council (MRC), Wellcome Trust and National Institute
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(‘CSMH’), a cross-Faculty initiative between the Faculty of Social Science and Public Policy (SSPP) and the Institute of Psychiatry, Psychology and Neuroscience (IoPPN). The centre aims to understand
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://baldwinlab.chem.ox.ac.uk/. About you Applicants must hold a PhD Biophysics, Chemistry or a related area, or be close to completion, prior to taking up your appointment. The research requires experience in NMR, familiarity
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computational cognitive neuroscience/psychology, computer science, or relevant quantitative field, and a demonstrably strong track record of scientific publication and novel idea generation. You will have strong
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fellowships. About You The ideal candidate will hold (or near completion of) a PhD/DPhil in computational cognitive neuroscience/psychology, computer science, or relevant quantitative field, and a demonstrably