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complex behaviours, including learning, in the small invertebrate model organism C. elegans. We have recently discovered a range of novel dopamine receptors in C. elegans and found that different receptors
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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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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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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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of computational and behavioural neuroscience with modelling and domestic chicks’ data. This position is funded by a Leverhulme Trust project entitled “Generalisation from limited experience: how to solve
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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
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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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2025. We seek to recruit a Research Associate specialising in statistical modelling and machine learning to join our multi-university multi-disciplinary team developing a groundbreaking technique based