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of Engineering, to work on an EPSRC funded project – ‘Engineering Twist'. The project aim is to develop experimental approaches to characterise enriched continuum models for mechanical metamaterials, and their
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structural), ECG, and genetics, to model disease trajectories and improve risk prediction in cardiomyopathies. The successful applicant will work closely with the PI to deliver research projects, supervise
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structural), ECG, and genetics, to model disease trajectories and improve risk prediction in cardiomyopathies. The successful applicant will work closely with the PI to deliver research projects, supervise
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of Engineering, to work on an EPSRC funded project - ‘Engineering Twist'. The project aim is to develop experimental approaches to characterise enriched continuum models for mechanical metamaterials, and their
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these bioinformatic experiments. Access to a high-performance computer will be provided. The candidate must be capable of generating complex molecular compound models in silico and using current molecular dynamic
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, or computational modelling. This post is based at the Department of Computer Science and on-site working is required. Remote and part-time working options must be agreed with Professor Nobuko Yoshida. What We Offer
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dedicated to development, translation and clinical application within medical imaging and computational modelling technologies. Our objective is to facilitate research and teaching guided by clinical
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optimisation techniques and AI-based models to support decision-making in microgrid design and operation. Working in collaboration with a leading global mission critical firm of engineers, this project offers
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and analysis of probabilistic and social choice models, help with the design and conduct of experiments, perform literature reviews, and contribute to the drafting of technical reports and publications
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with the possibility of renewal. This project addresses the high computational and energy costs of Large Language Models (LLMs) by developing more efficient training and inference methods, particularly