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aims to develop computational models to support the optimisation of plasma atomic layer deposition equipment. The PhD student will undertake numerical simulation, optimisation studies, and explore
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, this cohort of funded students will receive training in machine learning and AI methods at the University, together with training in the fundamentals of air traffic control at NATS, based at Whiteley
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techniques such as modular design and efficient fine-tuning. The project will also study the trade-offs between model efficiency, reasoning quality, and interpretability, developing methods that provide
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Ship design is a mature discipline with a long history of using tried and tested methods, demonstrated by thousands of successful examples in use today. However, the move towards more sustainable
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predictive performance, computational efficiency, and spatial resolution through algorithm optimisation, tuning, and refined covariates. Assess trade-offs between spatial resolution and other performance
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strong numerical, analytical and coding skills with undergraduate and masters degree in Mathematics, Earth System Sciences, Natural Sciences and related subject areas.
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background with strong remote-sensing, numerical, analytical and coding skills with undergraduate and masters degree in Mathematics, Earth System Sciences, Natural Sciences and related subject areas.
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qualification/experience in a related field of study and be able to demonstrate sufficient knowledge in the discipline and of research methods and techniques to work within established research programmes
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numerous discounts at leading retailers onsite gyms on all of our campus’ and a cycle to work scheme sector leading policies around maternity, adoption and shared parental leave (up to 26 weeks full pay
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, etc.), or the equivalent qualifications gained outside the UK, in a relevant area of Physical Science, Materials Science, or Engineering. You should be able to demonstrate some computational