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experts to acquire bespoke training and testing data; develop prototype solutions informed by the latest ideas in medical imaging AI, computer vision and robotic guidance; and evaluate models in simulated
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and social data with the aim to better understand energy use. The programme is an interdisciplinary collaboration between the School of Geography and the Environment (Oxford), the Department
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qualitative social science research, such as literature reviews, surveys, interviews, thematic analyses, researching and writing up case studies, data presentation, etc. Candidates also proficient in
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, fluorescent microscopy, etc.), as well as extensive experience in quantitative proteomics (both sample preparation and data analysis) is expected. As a postdoctoral researcher, you are expected be able
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project to develop a systematic framework for reconstructing the evolutionary histories of pathogens. The role involves using viral sequence data and models of sequence evolution to investigate both
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and leading a programme of numerical simulations relating to all aspects of our research on P-MoPAs; using particle-in-cell computer codes hosted on local and national high-performance computing
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technologies have exploded in recent years, generating multi-dimensional data from millions of cells and thousands of molecular features. Understanding these data and harnessing their insights remains an ongoing
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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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detailed T-cell phenotyping and functional assays • Conduct mechanistic studies using molecular and cellular immunology techniques • Contribute to data analysis, presentation, and publication
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and Mind Building, South Parks Road, Oxford Applicants must hold a PhD in Microbiology and/or Molecular biology and will be responsible for providing microbiological data to facilitate the design of new