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. The successful applicant will have the opportunity to collaborate with researchers across the College of Medicine and Health in cancer and genomic, cardiovascular and metabolic sciences, as well as national and
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support the development of AI-driven and data-driven approaches for the discovery and design of functional materials. The role will involve the development and application of machine learning models, high
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the Department’s research investment, oversee the development of Annual Modal Research Plans, and provide opportunities for research collaboration with public and private sector partners. The areas of learning
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independently or collaboratively in an interdisciplinary team Self-motivated to learn, easily adapted to new tasks, and interested in solving challenging scientific problems. Good communication skills and
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managing the needs of the current patient population in collaboration with the team. They are an integral member of and will work collaboratively with, a multidisciplinary health care team. The APP Fellow is
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media. You will join the UKRI/AHRC-funded BRAID P3R project, working within the CoSTAR National Lab as part of a collaboration between the University of Surrey and Royal Holloway, University of London
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to disease prediction and prevention. Through our Team Science approach, we have achieved breakthrough discoveries in five key areas: neuromodulation (reinforcement learning), critical period mechanisms
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artificial intelligence and machine learning (AI/ML) models that predict therapeutic response, identify clinically actionable patient subgroups, and support personalized treatment strategies. Through
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The AI Centre for Educational Technologies (AICET) is a research centre that is focused on developing technologies to improve learning. AICET collaborates with the Singapore Ministry of Education
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funded project, in collaboration with the Rosetrees Trust, entitled “Modifying Physical Education (PE) to enhance cardiometabolic health, cognition and academic outcomes in young people living with