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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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experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models
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experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models
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for medicine use before and during pregnancy. This postholder would work primarily on a recently funded programme of work to develop a novel approach to understanding and communicating the Safety of Medicines in
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the risks. You will have: a PhD in one of the relevant STEM disciplines, such as mathematics, statistics, computer sciences, theoretical food, ecological or physical sciences, etc. skills in mathematical
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. The Department delivers undergraduate and postgraduate programmes in Sociology, Criminology and Social Work and supports the delivery of a faculty research methods programme as part of the collaborative NINEDTP
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science, or specific skills to a team delivering a project or program. Through this work, you will build scientific independence, develop new science and leadership skills, and establish a growing
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About the Role You will develop and apply novel computational methods to quantify the societal impact of fundamental science discoveries. Candidates close to completion of their PhD will initially
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comparing these approaches in terms of computational complexity, implementability, effectiveness, and interpretability, this project aims to establish solid mathematical criteria to inform novel design and
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the study of problems in quantum many-body physics through the lens of quantum information and quantum computing? Do you enjoy analyzing complex quantum mechanical systems through a combination of