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about to obtain, a First or Upper Second-Class UK Honours degree, or the equivalent qualifications gained outside the UK, in Statistics, Mathematics, Data Science or Computer Science. To apply, please
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engineering knowledge. Funding support We are offering home fees and UKRI minimum stipend. Further information Please contact Tao Yang ezzty@exmail.nottingham.ac.uk for further information Closing date 16
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Human Behaviour in projects targeting social good. Research at N/LAB focuses on the development and application of innovative computational methods using Big Data, Behavioural Science and Machine Learning
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of Engineering at the University of Birmingham and delivered in collaboration with industrial partners and the Quantum Technology Hub in Sensing, Imaging and Timing (QuSIT) – one of five national hubs funded by
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control. Joining the leading researchers in the Centre for Engineering Research at the University of Hertfordshire, collaborating with our industrial partners and becoming a member of the vibrant doctoral
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conducting the qualitative interviews with patients and analysing the interview data. You will be presenting that data to the study team at regular meetings and contributing to the intervention and app
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for cardiovascular applications. You will build on our group’s expertise on Physics-Informed Machine Learning (PIML), a powerful approach that combines data-driven AI with the rigour of physical and physiological
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fit if you: Have a background in Biochemistry, biomedical sciences, organic chemistry and biophysics Are desire to explore the biochemical composition and biological activity of GAGs Are confident
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system using deep learning (DL). The project’s objectives include generating training data from synthetic datasets and real-world images (cadaver and actual intraoperative THR images), developing a marker
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of innovative computational methods using Big Data, Behavioural Science and Machine Learning to understand behaviour through the lens of digital footprint/“smart data” datasets, cutting across sectors ranging