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on identifying and discovering patient sub-cohorts within an electronic health record database. This discovery process will take place via the design of deep clustering algorithms based on state-of-the-art
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capable of supporting and collaborating with humans in complex, real-world settings. You will be responsible for researching and developing novel algorithms and techniques to achieve the project’s
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solvers • Implementing and analysing online optimisation algorithms for real-time grid balancing • Liaising with project partners (NESO and University of Strathclyde) Essential selection
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for real-time human data processing in interactive settings. Technical expertise in areas such as electrophysiological recording, VR paradigm design, closed-loop algorithm development, or clinical
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Develop industrial process digital twin models based on the fusion of mechanistic and data-driven approaches. Develop predictive maintenance and fault diagnosis algorithms for critical equipment (e.g
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/DPhil in a subject relevant to Biochemistry and have specialist knowledge on an aspect which is pertinent to the project, such as chromatin biology, molecular evolutionary analysis, molecular dynamics