80 programming-"the"-"DAAD"-"Diamond-Light-Source" Postdoctoral positions at University of Oxford
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into practical methods for smarter testing and control. You’ll need to have expertise in modelling and simulation of dynamic systems, strong programming skills, and the ability to communicate your research clearly
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researchers in the Future of Food programme at the Oxford Martin School. You must hold or be close to the completion of a doctoral degree in a relevant field (e.g. data science, industrial ecology, geography
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role in participating in the exchange programme with Johns Hopkins University. You will also be responsible for contributing new research project ideas, managing your own administrative activities and
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mathematical skills, a strong understanding of mechanics and an ability to undertake scientific programming. You will have excellent written and oral communication skills, and an ability to work both
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surveys, early universe and gravitational physics. Good programming experience, an enthusiasm for coding and data analysis, and the ability to work in a large collaboration, are particularly relevant
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completed, or be close to completing, a PhD/DPhil in a relevant quantitative field together with a demonstrable track record in studying humans and machine learning models. Advanced programming and
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have strong quantitative analysis skills, using statistical programming packages such as R, as well as excellent communication skills. This is a full time, fixed term post (part time considered) for 3
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/test articles), intrusive probes, and optical diagnostics. You’ll plan and run test campaigns, analyse data to advance understanding of material–flow interaction, and disseminate results in seminars
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strategic programme. Through multiomic and spatial biology exploration of temporally distinct samples from clinical trials and advanced biological models, an international consortium of leading colorectal
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Colorectal Cancer - Stratification of Therapies through Adaptive Responses (CRC-STARS) programme, developing and applying cutting-edge mathematical methods to spatial transcriptomics imaging data in order to