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to protect our planet from asteroid hazards. The aim of the project is to deliver and validate of an onboard astrodynamics GNC software for autonomous proximity operations around minor celestial bodies
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autonomous sensing systems. The project requires experience with setting up sensing hardware, software defined radio systems and other lab equipment for data collection in addition to experience of programming
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findings to academic and industrial audiences, publish in leading journals, and actively contribute to the development and dissemination of open-source software. Additionally, you will support junior
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simulations to improve on existing power usage models. This research will be a key component of making computing more sustainable by providing novel insights into the energy usage of scientific software and
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used. AI methods for generating regulatory hypotheses between genes, hormones and physical properties will also be developed. Applicants must have/be close to obtaining a PhD or MPhil in Computational
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, epigenomics and transcriptomics from these models alongside extensive human tumour collections. You will be PhD-qualified, or have submitted your PhD thesis for examination at the point of commencing this post
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used. AI methods for generating regulatory hypotheses between genes, hormones and physical properties will also be developed. Applicants must have/be close to obtaining a PhD or MPhil in Computational
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economic studies funded by the UK National Institute for Health and Care Research. Experience of conducting economic evaluations using suitable statistical software (e.g. STATA, R or SAS) is essential
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the decision analytic modelling field research field and contribute to high quality reports for funding bodies and peer-reviewed outputs. You will hold a DPhil/PhD in health economics or a related quantitative
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the decision analytic modelling field research field and contribute to high quality reports for funding bodies and peer-reviewed outputs. You will hold a DPhil/PhD in health economics or a related quantitative