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students and PhD students. This post is fixed-term for 2 years, to start no later than 1 January 2027. Applicants will have, or be close to completion of a PhD, together with relevant experience in the area
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combined with AI methods for adaptive rather than static surveillance design. This project is particularly exciting because it combines new advances in methodologies with direct applications in public health
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to work on the discovery of new superconducting materials with high critical temperatures, using novel methods and concepts such as machine learning and quantum geometry. The project is related to large
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outcomes, communicate complex information, orally, in writing and electronically and prepare proposals and applications to external bodies. Applicants will possess a relevant PhD or possess an equivalent
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students and PhD students. This post is fixed-term for 2 years, to start no later than 1st January 2027. Applicants will have, or be close to completion of a PhD, together with relevant experience in
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. They will be expected to guide more junior colleagues, including postdocs, research assistants, PhD and project students. The research may involve either analytical work, numerical computations or both
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reproducible research software and scalable data analysis pipelines in Python for machine learning and interpretability research. These tools will support systematic investigation of model behaviour and enable
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microscope, single molecule TIRF microscopy and analysis of RNA-protein interactions by techniques including FRET. Length of advert - 2 weeks About you You will hold a high‑quality first degree and PhD in
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, PhD students, and/or project volunteers. About You You will have or be close to the completion of a relevant PhD/DPhil, in applied health research / mental health research together with relevant
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colleagues in the research group, as appropriate, to identify areas for research, develop new research methods and extend the research portfolio. To deal with problems that may affect the achievement