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Field
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This project addresses a fundamental question in digital twin development for fusion energy systems: the relative roles and limitations of physics-based models, experimental data, and AI-driven
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Fully Funded PhD Studentship (Home Fees) Project Title: Developing Fair and Robust Cancer Risk Prediction Models Using Health Data Supervisor: Professor Angela Wood (Professor of Biostatistics and
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. B1 Grundstufe (praedoc) Limited until: 31.10.2030 Reference no.: 6201 Are you interested in the study of problems in quantum many-body physics through the lens of quantum information and quantum
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an important part of a large international medical-device industry, creating substantial demand for new methods of obtaining physiological information accurately, continuously and with low-power sensing
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21 Sep 2026 Job Information Organisation/Company Imperial College London Department Department of Physics Research Field Physics » Optics Researcher Profile First Stage Researcher (R1) Positions PhD
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develop AI tools for the interrogation of subcellular proteomics data. We are interested to hear from candidates with experience in probabilistic or statistical modelling of complex biological data, such as
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’ training needs and existing care pathways. The PhD student will also use existing longitudinal data to investigate the impact of accessing versus not accessing mental health support, on children and parents
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developing the first observation-driven, AI-ready global river data infrastructure. Reporting to Professor Louise Slater, you will lead research combining large-scale Earth observation data, global hydrography
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, combining biodiversity surveys, animal movement data, landscape modelling and remote sensing to understand how trees within agricultural landscapes influence wildlife movement and landscape connectivity
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investigate the wildlife connectivity potential of tree-based agricultural systems, combining biodiversity surveys, animal movement data, landscape modelling and remote sensing to understand how trees within