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Neuroscience is UK’s 2nd largest Neuroscience school with over 500 researcher and 200 PhD students. It is one of three schools at the Institute of Psychiatry, Psychology & Neuroscience. We are ranked 4th in
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into improvements in health care. • To assist in the training of PhD students and other members of the LMB. Key responsibilities: Within the overall direction of the programme, the group, the remit of the project
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) Qualifications Formal postgraduate qualification in a relevant discipline PhD in Health Economics, Epidemiology or Evidence Synthesis or a closely related quantitative subject or equivalent experience
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students (Desirable) Teaching experience at undergraduate and postgraduate level in an academic setting (Desirable) Qualifications Formal postgraduate qualification in a relevant discipline PhD in Health
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confidence and ability to manage your own workloads to ensure outputs. You will receive practical and formal training, gain marketable skills, broaden your knowledge and expertise within an industrially
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holder will work closely with the Graduate School to manage and process all prospective PGR student/PhD researcher applications (including applications for visiting PGR students from other institutions
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of psychotherapeutic methods (with a behavioral, systemic or humanistic approach). The research profile should be empirically oriented and be compatible with the Faculty's thematic areas in terms of content and
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Computer Science). Outstanding candidates who do not have a PhD but wish to pursue one on the topic of this project will also be considered. x Knowledge and experience in software developments or formal
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Artificial Intelligence (AI). We interpret a substantial connection to AI broadly to include, for example, the intersection of AI and philosophy of science, AI and logic/formal methods, AI and moral and
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pertaining to organizational design decisions relevant to firms operating in (technologically) innovative environments. We are agnostic to methods and pursue formally analytical, simulation-based, ethnographic