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experience of data analysis of large, complex healthcare datasets alongside experience of writing papers for peer-reviewed journals. It is essential that candidates have a strong working knowledge of research
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biased narratives in public discourse sustain intergroup conflict and inequality? How do large-scale upheavals shape our collective identities and narratives? More information is available here . We
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Digital Twin for electric vehicle applications . The role will focus on utilizing novel machine learning models, large language models, and data science algorithms to develop battery models, optimization
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longitudinal clinical data and biological sample collections (e.g. Biomarkers and Stratification To Optimise outcomes in Psoriasis (BSTOP) study, mySkinomics study, as well as interventional studies, e.g. PLAN
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large-scale whole genome sequencing datasets, applying cutting-edge bioinformatics approaches to study structural variants. The fellow will play a key role in advancing our understanding of evolutionary
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decades, as well as registry data linked to multiple large surveys with longitudinal individual-level data, school-level aggregated data, and genetic data. The successful candidate is expected to use state
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utilise modelling techniques using phenotypic information derived from the electronic clinical records for large populations with long term conditions. The post holder will undertake translational research
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a multidisciplinary team under the guidance of Brijesh Dongol (PI) and Gregory Chockler (co-I), as well as a large team of academics (Imperial, Kent, Sheffield, MPI-SWS, Cornell, IMDEA, etc) and
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experimental studies, collecting data from human participants and analysing crossing behaviour as well as head/eye tracking data? Are you interested in joining the vibrant and world-renowned Human Factors and
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been recent rise in vision foundation models such as GPT-4o, Instruct-BLIP and LLava. However, training foundation models has significant environmental costs tied to large scale datasets as highlighted