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diversity of platforms (e.g., ground stations, unmanned aerial vehicles, fixed wing aircraft, as well as satellite imagery). It is also expected that the post holder will advise on- and develop- models
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machine-learning models to investigate how brain, environment and social factors influence cognition, ageing and neurodegenerative disease. The role will contribute primarily to WP6 and related analytical
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and the African turquoise killifish to model human cardiovascular diseases, polycystic kidney disease (PKD), and cardiac aging. Our research aims to uncover the molecular and cellular mechanisms
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Location: The Francis Crick Institute, London Short summary We are seeking an ambitious Postdoctoral Fellow to develop the next generation of deep mechanistic models (DMMs; Fabrini & Fröhlich
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internal institution systems may be submitted. Click here for detailed information about acceptable transcripts. A current resume/CV, including academic history, employment history, relevant experiences
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combining field sampling with laboratory experiments and statistical modelling to quantify genetic variation in complex traits, the candidate will test whether these contrasting histories have driven
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substantial funding for access to state-of-the-art AI models and computing infrastructure. About you We are interested in candidates with expertise in one or more of interactive theorem proving, formal
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, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale knowledge graphs, and large language models. Fellows will also have the opportunity to apply
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strong team dedicated to pioneering innovative experimental and modeling techniques that bridge the gap between laboratory-scale physics and field-scale implementation. Our mission centers on developing
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solutions for offshore wind turbines, enabling to enhance their structural awareness, real-time reliability assessment, and predictive maintenance decision support through integrated sensing, modelling, and