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science, engineering, or a related discipline, with significant postdoctoral research experience. The ideal candidate will have strong expertise in computational biology, machine learning, and quantitative analysis
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goals for the game changing impact of our science globally. Our employees enjoy access to state-of-the-art technology and a diverse range of specialist training opportunities, including support for
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, Engineering, or a closely related discipline. You will be a materials or physical scientist with a strong track record in applying deep learning to computer vision problems, ideally within battery
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engineering of host plants. The successful candidate will use carbon tracing, single-cell transcriptomics approaches, and targeted mutagenesis in the model crop rice to address these questions. We are looking
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University Hospital) will support TomoGrav’s planned technology transfers to, respectively, SKA, space geodesy, and MRI. The partners will actively participate to the research and host the postdoctoral
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testing for all three projects. Applicants should hold a relevant PhD/DPhil (or be close to completion) in engineering or a related discipline. Post-qualification research experience and a strong
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chemistry or chemical engineering, a strong publication record, a pro-active approach and strong expertise in gas phase heterogeneous catalyst testing and in catalyst synthesis and characterisation. The post
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and Botswana International University of Science and Technology. A PhD in a Biological Science, Computer Science, Mathematics or Statistics, and relevant experience modelling population dynamics
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research project lead by Oxford Materials (Professors Robert House (PI), Saiful Islam, Peter Bruce), with UCL Chemical Engineering (Dr Rhod Jervis) and 4 industrial partners that brings together expertise in
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effects while building machine-learning-ready kinetic datasets for predictive catalyst design. You should have a PhD (or about to obtain) in Chemistry or field related to this project (Chemical Engineering