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studentship, commencing in October 2025 as part of the second EnerHy intake, is based at the University of Strathclyde and centres on advanced analytics for wind energy data. Research Project Overview The wind
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an early warning system of dementia, to be exploited within existing healthcare pathways to trigger early intervention. Skills acquisition The studentship will provide training in data-analytics, statistics
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critical steps of gastrulation and early development. Creating iPSC lines with mutations in elements of the GAG biosynthetic machinery. Applying novel GAG analytical technologies to investigate how changes
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the unique opportunity to develop skills in analytical, statistical and data science techniques, working with real world data to provide recommendations for UKHSA on how pharmacy OTC data could be used
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often fail to preserve the fidelity of combined datasets, leading to loss of crucial information. This proposal aligns directly with the CAMS Data Analytics Theme and the Grand Challenge of using machine
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biology experience with laboratory-based research (e.g., cell culturing, molecular techniques, bioinformatics, flow cytometry) ability to work independently and as part of a research team strong analytical
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Primary supervisor - Prof Kate Kemsley Join us to research and develop advanced analytical methods for tackling food fraud head-on! Economically motivated adulteration of foods is a significant
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biosynthetic machinery Applying novel GAG analytical technologies to investigate how changes in GAG structure and organisation drive and/or respond to shifting developmental stages. Working Environment: Based
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& robust control, and learning for dynamics & control. The main task of the PhD student will be to develop sound data-driven methodologies for learning control policies with provable guarantees
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to enable discoveries that improve people’s lives. Its 20-year vision is for large-scale data and advanced analytics to benefit every patient interaction, clinical trial, and biomedical discovery and to