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Field
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contributing to multi-site or international collaborative research programmes, particularly in maternal, perinatal, or population health Experience applying machine learning or AI methods in healthcare research
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, learning under uncertainty) that is of an international standard, and that is carried out expertly, rigorously and in accordance with ethical guidelines. You will also participate actively in the lab
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and cellular mechanisms shaping spatial and temporal trajectories of liver regeneration and cancer. Linking computer simulations with experimental observations will further uncover intrinsic and
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. This PhD project will build directly on this work by using ideas from machine learning—originally developed to study the movement of larger organisms—to understand how bacteria process information in
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device health status through condition monitoring. AI techniques such as machine learning will be used to optimise gate driver performance and to map gate drive signal attributes to power device health
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the Ice Sheet and Sea Level System Model (ISSM). and/or The development of automated (e.g., machine learning) approaches for mapping glacier-surface morphologies on Mars. You will join a cutting-edge
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Experience in undertaking independent research. Desirable: F1 Experience of digital health methods, including AI and machine learning. F2 An emerging national or international reputation. Please note: This is
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good understanding of the needs of international students, and ideally have awareness of teaching and learning within a UK university context. You should have significant English Language Teaching (ELT
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intelligence (AI) is changing how we understand and improve healthcare. This project will use the latest advances in AI to develop new tools that can learn from many different types of medical information
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such as: Systems security, Security engineering, Security testing, Computer forensics, AI for security and privacy, Security and privacy of AI. Our department addresses computer science challenges from a