882 phd-rehabilitation-engineering-computer-science Fellowship positions in United Kingdom
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offloading strategy via simulations and live demonstrations. Job Requirements A Ph.D degree in Computer Engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly analytical
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BCAST and research engineers from industry. The successful candidate is preferred to have a PhD degree in materials science and engineering, mechanical engineering or another suitable engineering
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. Candidates should hold a PhD (or equivalent) in Chemistry, Chemical Engineering, Materials Engineering, or a closely related field from a research-led university. Advanced knowledge in bitumen chemist is
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) that combines a mix of remote and regular on-campus working. The salary for this post is UE07 £41,064 to £48,822 per annum. Your skills and attributes for success: PhD in Neuroscience is required with
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for the development and day-to-day management of the system which will initially use face recognition technology. As such, the candidate will be expected to have excellent software engineering/computational skills as
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interviews will be arranged for early October. About you The successful applicant will have a PhD in electronic engineering, physics, or a related subject. The applicant will have experience in designing
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, 2) design and evaluation of technology to reduce the carbon footprint of the health and social care system. Qualifications/ experience: PhD in in a subject relating to health services research
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for candidates to have the following skills and experience: Essential criteria PhD in bioinformatics, computational biology, or a related discipline Extensive experience and expertise in applying/developing and
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College of Engineering, Design and Physical Sciences Location: Brunel University of London, Uxbridge Campus Placement: Fixed term (12 months), Full–time, up to £40,757 per annum Brunel University
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: Essential criteria PhD in bioinformatics, computational biology, or a related discipline Extensive experience and expertise in applying/developing and training deep learning models on biological, chemical or