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whole exome/genome sequence data in both clinical genetic studies and/or large-scale population studies, such as the UK Biobank Study. Applicants must have a degree in genetic epidemiology, statistical
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. Experience of working with large multimodal datasets. Interest in human-computer interaction and human-centred system design. Strong communication and organisational skills. While is not necessary to have
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. This leaves manufacturers and battery management system developers with limited data on which to define safe operating windows, while the computational models intended to predict plating–stripping dynamics
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missing data in large-scale healthcare datasets. The student will investigate how data completeness varies by patient and healthcare setting, evaluate its impact on cancer risk prediction, and develop new
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resilient infrastructure. The successful candidate will join a large dynamic team of researchers working on different challenges. The key responsibilities are driving, planning and conducting innovative
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processes for manufacturing large area meta-materials. In particular, we will focus on roll-to-roll (R2R) processing methods, which we seek to combine with emerging bottom self-assembly processes and top-down
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green finance and regional development. Key Responsibilities for the role include: Data collection, cleaning, and merging from large-scale microdata sources (e.g., patents, dissertations). Developing new
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About the project: Extreme Weather Storylines via Generative AI Supervisor: Dr Tobias Grafke, University of Warwick Generative machine learning techniques, as known for example from large language
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. The successful applicant will gain expertise in analysing large geological datasets, integrating multidisciplinary information and evaluating geological storage systems at regional scale. The outcomes will
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holder will be located in Central Cambridge, Cambridgeshire, UK. The role involves: Designing and carrying out quantitative single-cell infection experiments, Analysing large microscopy datasets Developing