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the UKRI Future Leaders Fellowship “AI-Driven Inference for Gravitational Waves: Accelerating Discoveries in Fundamental Physics” (PI: S Green). We believe that talented and inclusive teams deliver
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PhD or equivalent in a relevant subject area. an extensive track record in the development and delivery of teaching units with proven ability to provide effective leadership and management of groups and
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the University’s international reputation as a hub for cutting-edge research. Candidates must have a PhD degree in Power Electronics, Machines, and Drives or a closely related field, with a proven track record in
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engineering and have or be in the process of obtaining a related PhD and a track record of successful research. They will be computer literate with strong communications skills and a proven ability to work as
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be considered. It is required that the candidate has strong academic experience and evidence of strong track record in his or her area of research. The appointment will be offered to the best qualified
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track record in brain connectivity mapping using diffusion MRI, with a portfolio of research programmes, including funding from the European Research Council (ERC) that supports this position
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experiences whilst enjoying snacks. This will include developing techniques to track and understand position of the face and mouth in 3D, and potentially tie these metrics to associated robotic technologies
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based microcontrollers power converter topologies. They will also possess a consistent track record of published research in reviewed publications. You will be a dynamic self-starter, exceptionally well
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possess a consistent track record of published research in reviewed publications. You will be a dynamic self-starter, exceptionally well-organised and have a positive attitude. Working with work with
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have access to world-class laboratories, industrial-scale deposition systems and unique characterisation facilities. With a strong track record in energy innovation and industry partnerships