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, sociology, economics or a related discipline. The project is based on a collaboration between Sheffield University Management School (SUMS, United Kingdom) and University of São Paulo (USP, Brazil
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The burden of medical plastic waste has become an increasingly pressing concern in recent years. The healthcare industry relies heavily on single-use plastic items due to their convenience and
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or electronic engineering, machine learning, medical physics or neuroscience. Knowledge of electronics is essential. Strong programming skills (MATLAB is essential) & Phyton (TensorFlow library, desirable
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scores that help tailor diagnostics and therapeutics for different diseases. Through being a member of Dr Morsy research team at the School of Pharmacy and Medical Sciences, The student will be a member of
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useful for pregnant populations and sportswear manufacturers in providing knowledge for users and developing new and innovative products. The studentship will appeal to students with a sports science
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-month project within mental health research using a neuroscience or social science approach. The successful candidate will join a vibrant community of postgraduate researchers and will benefit from
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. Eligibility Criteria A 2:1 honours degree, or international equivalent, in a relevant subject (e.g. health sciences, epidemiology, statistics, psychology, medicine, pharmacy, nursing, midwifery, allied health
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DoS: Dr Eve Kelland ([email protected] ) 2nd Supervisor: Professor David Parkinson ([email protected] ) Applications are invited for a three-yearPhD studentship. The studentship will start on 1st October 2024. Project Description Multiple Sclerosis (MS) is a complex...
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at the surface of implanted medical devices. Implanted medical devices are crucial in healthcare, valued at around £400 billion globally, however there is a high failure rate, often due to the foreign body
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About the Project Remote patient monitoring facilitated by mobile sensing technology is on the way to changing how patients are monitored and treated. By analysing extensive data from wearable