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of degradation pathways and shelf-life prediction. The aim of project is the safe integration of machine learning methods within the biopharmaceutical development process. This project offers an opportunity to be
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the university, genomic and metabolomic measures, offering novel potential to explore the physiological basis for imaging measures and apply machine learning in a radiological context. You will join an established
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in this state-of-the-art facility for advanced electrical machines for power generation, marine, aerospace and automotive industries. About You Candidates should hold or be shortly due to obtain a PhD
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. The aim of project is the safe integration of machine learning methods within the biopharmaceutical development process. This project offers an opportunity to be at the forefront of interdisciplinary
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developing machine learning or data science approaches for patient stratification and genetic association analyses using cardiac magnetic resonance imaging in biobank populations. Successful applicants will
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governmental or charitable funders. This post is tailored for applicants who have a research interest in developing machine learning or data science approaches for patient stratification and genetic association
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Health Regulations. Assist in project resource requirements and managing student projects. Job Requirements: Have a PhD Degree in Computer Engineering/Computer Science/Electrical Engineering or equivalent
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or machine learning methods Advanced knowledge of electronic healthcare records and their use in development and validation of risk prediction models Knowledge in application of econometrics in research
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students. Selection criteria: • PhD/DPhil in a relevant field (or near completion). • Strong project management and communication skills. • Multidisciplinary and collaborative mindset
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students. Selection criteria: PhD/DPhil in a relevant field (or near completion). Strong project management and communication skills. Multidisciplinary and collaborative mindset. Commitment to EDI and