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suitable to candidates with a wide range of backgrounds such as but are not limited to: climate science, psychology, mathematics, geography, environmental science, law, computer science, public health
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integrates machine learning and statistics to improve the efficiency and scalability of statistical algorithms. The project will develop innovative techniques to accelerate computational methods in uncertainty
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the Computational Foundry, a world-class centre for computational research, part-funded by the European Regional Development Fund through Welsh Government. The brand-new building of the Computational Foundry provides
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computer literacy, good inter-personal communications skills. Desirable skills: A Master in Health Economics with experience in cost effective analyses. Funding notes The three year studentship covers UK
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, spanning domains from automotive and avionics to healthcare, increasingly rely on distributed and multi-layered control architectures. These systems comprise interconnected computing nodes, actuators and
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clearance level. The Engineering Doctorate Researcher will follow the EngD in Model-Based Systems Engineering Programme. They will be based at NPL. Entry requirements: A minimum of an upper-class honours
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training in computational tools and statistical methods over the course of the project. The project includes placements at NPL and Waters-TA Instruments, with opportunities to work in state-of-the-art
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, this is only available to those eligible for UK fees. All applications should be made online via the above ‘Apply’ button. Under Campus, please select ‘Loughborough’ and select Programme ‘Chemistry’ Please
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to produce cutting-edge research. Prospective applicants must: Hold a good honours degree in an appropriate subject (including Computer Science, Physics, Maths, Engineering) Knowledge of modern machine
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from other acquired brain injuries (e.g., traumatic brain injury, brain tumour, stroke) – this work package will include quantitative and qualitative studies; second, to develop a training programme for