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training and have opportunities to participate in faculty development programmes. The fellowship is tenable for one year. On an exception basis, a two-year programme may be supported. Service Commitment One
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. The successful candidate will become an active member of the Energy, Power and Intelligent Control (EPIC) research centre within the School of Electronics, Electrical Engineering and Computer Science (EEECS
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at national and international conferences. The project is based around constructing physics-informed neural networks (PINNs) to model the fluid dynamics of Earth’s core where the global magnetic field is
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Health programme (Chief Investigator, Dr Matthew Franklin ) to evaluate the (cost-)effectiveness of mental health treatments used with Talking Therapies for anxiety and depression services using NHS real
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-related factors of physical function and sarcopenia in older African adults. MUFASSA is a sub-programme of the Fractures in Sub-Saharan Africa: epidemiology, economic impact and ethnography (Fractures-E3
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quantitative techniques (e.g., NLP, classification, clustering), statistical modelling, and other computational techniques Process large scale text data sets in multiple languages Create documentation for data
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learning, computer science, physics, statistics, mathematics or related field. Demonstrated experience designing and developing novel machine learning and/or computer vision methods for either computational
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clinical, nutrition and lifestyle-related factors of physical function and sarcopenia in older African adults. MUFASSA is a sub-programme of the Fractures in Sub-Saharan Africa: epidemiology, economic impact
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Programme. The NBRC is a partnership between Nottingham University Hospitals NHS Trust and the University of Nottingham funded by National Institute for Health and Care Research (NIHR). The mission
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learning, computer science, physics, statistics, mathematics or related field. Demonstrated experience designing and developing novel machine learning and/or computer vision methods for either computational