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interdisciplinary PhD is highly desirable. PhD equivalence is acceptable but will need to be demonstrated through certified evidence of substantial training and experience that has qualified candidates to plan
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model checkers; proofs of safety and/or security properties; programming languages and/or type systems; concurrent and/or distributed algorithms; and related topics. The successful applicant will work in
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training and fine-tuning large language models (LLMs) to extract structured clinical concepts from unstructured EHR, pathology, and radiology reports. The role involves publishing in high-impact, peer
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training and fine-tuning large language models (LLMs) to extract structured clinical concepts from unstructured EHR, pathology, and radiology reports. The role involves publishing in high-impact, peer
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, in a relevant topic and relevant experience with mathematical modelling of infectious diseases. Strong knowledge of a programming language (e.g. R, Python) is essential. Experience in mathematical
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. Candidates must also have excellent programming skills in a relevant scientific language, such as Mathematica or Python, to facilitate advanced data analysis of measurement outputs. Apart from being able
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of epidemiological modelling and data analysis C2 Up-to-date knowledge of epidemiological modelling approaches C3 Knowledge of relevant programming languages for model development, for example Java, R, C++, Julia C4
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date: 19th June 2025 Background To create and contribute to the creation of knowledge by undertaking a specified range of activities within an established research programme and/or specific research
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and commercial tools (e.g. XCMS, MZmine, Compound Discoverer, GNPS, SIRIUS, etc). Proficiency in one or more programming languages (e.g. R, Python). Experience with continuous integration and best
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financial support. Plan, publish and/or execute high quality research. Project manage research activities, and/or supervise other research staff where appropriate. Present high-quality findings in