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We are seeking a talented and motivated researcher to join the Mead Group to contribute to a major research programme, focused on understanding and preventing disease progression in
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on transplant using multimodal medical data. You will be responsible for literature review, data cleaning, model development and implementation. You should possess a relevant PhD (or near completion) in
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to the study and teaching of the language and literature of ancient Greece and Rome, including Late Antiquity, as well as the late, medieval, and Neo-Latin language and literature. At the core of the program is
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require close cooperation with other research groups. The position requires PhD in computer science, engineering, or a related field Excellent research track record in AI and sustainability or cloud
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and PhD students) and openly share expertise knowledge with team members (e.g. Post-docs). Collaborate with other two post-docs working in this research programme, to deliver on project aims. Contribute
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. The role includes overseas travel to both partner countries as part of the research programme. We are seeking an enthusiastic and experienced researcher with expertise in genomics and bioinformatics, large
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The Role Applications are invited for a Postdoctoral Research Associate position in the Department of Engineering, with a focus on digital twin modelling for marine engines and propulsion systems
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on a project funded by the ERC Advanced Grant 'RheoYield'. The position is to commence in September 2025 or as soon as possible thereafter. Its overall aims will be to understand the deformation and flow
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of the intellectual environment, capital equipment, technical expertise and excellent infrastructure in place at the MRC BNDU and OxCIN. In addition to having a PhD (or M.D.) or equivalent qualification in a relevant
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Postdoctoral Researcher in Machine Learning of Isomerization in Porous Molecular Framework Materials
broad range of applications. Computational chemistry and Machine Learning increasingly underlies MFM research to search or screen candidate MFMs prior to synthesis. A major drawback when applying