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vulnerabilities (including to security and privacy) that may be introduced when AI is used to process data from wearable devices such as ‘smart glasses’. The project involves academics from Universities
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these bioinformatic experiments. Access to a high-performance computer will be provided. The candidate must be capable of generating complex molecular compound models in silico and using current molecular dynamic
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. Visit the Centre for Research Staff Development for more information. About you To be successful in this role, we are looking for candidates to have the following skills and experience: Essential
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for all. Find out more about the benefits of working at the University and what it is like to live and work in the Durham area on our Why Join Us? - Information Page The Role This scheme offers up to 6
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stakeholders. The successful applicant will be expected to lead and develop qualitative research activities, data analysis and project support. The applicant will have responsibility for leading research
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neurosurgical centre. In this role the successful candidate will develop deep learning algorithms and validate models on diverse clinical data which include magnetic resonance imaging (MRI) and computed
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will develop deep learning algorithms and validate models on diverse clinical data which include magnetic resonance imaging (MRI) and computed tomography (CT). In this role the successful candidate will
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to model immune-mediated kidney injury. Quantitative and reproducible read-outs from these assays will be correlated with human kidney ‘omics data to evaluate the impact of pathway modulation, ultimately
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, including molecular clouds (properties, formation, evolution), dynamics (supermassive black hole mass measurements, gas flows, active galactic nucleus feedback), and any other facets of the data not yet
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Prof Jim McElwaine (Woods Hole, USA). The project involves developing and maintaining radar equipment designed to capture quantitative data on pyroclastic density currents during volcanic eruptions