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fully funded PhD research studentship in Physics-Informed Machine Learning for Cardiovascular Medicine. This opportunity is open to UK (Home) candidates only. Project Overview Arrhythmias are disorders
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, and drug discovery? We are excited to offer a PhD position tailored for a motivated candidate eager to push the boundaries of structure-based drug design using cutting-edge machine learning techniques
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Your Job: Develop AI pipelines that translate -omic signatures into dynamic model parameters Implement reinforcement-learning agents that optimise model performance Collaborate closely with
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Job Description Are you interested in developing novel machine learning methodologies that are scalable, reliable and explainable and that can address imminent challenges? Responsibilities and
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scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available to UK (Home) candidates only. Fully-supervised AI techniques have shown remarkable success in
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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Funding for: UK/Home Students We invite applications for a fully funded PhD research scholarship in “Unsupervised Machine Learning for Cardiovascular Image Analysis”. This opportunity is available
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fully funded PhD research studentship in Physics-Informed Machine Learning for Cardiovascular Medicine. This opportunity is open to UK (Home) candidates only. Project Overview Arrhythmias are disorders
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The Network Analysis and Modelling uses machine learning to investigate how genetic variation shapes gene regulation, protein function, and, ultimately, observable plant traits. We are seeking a