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intelligent sensing, followed by detection of the important events.In the light of autonomous decision making, the project aims at developing machine learning algorithms for knowledge extraction from data
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complexity, classical control techniques cannot be easily applied because of computational bottlenecks or an absence of suitable prediction models. Distributed control approaches have been conceived to handle
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high-throughput screening using genetic and imaging tools. Apply molecular and cellular assays to study inflammatory processes. Analyse integrative omics datasets using bioinformatics and machine
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Computational Fluid Dynamics modelling of free surface flows over packing materials in a CO2 absorber School of Mechanical, Aerospace and Civil Engineering PhD Research Project Self Funded Prof
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high-throughput screening using genetic and imaging tools. Apply molecular and cellular assays to study inflammatory processes. Analyse integrative omics datasets using bioinformatics and machine
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. This project uses zebrafish as a model to identify the signals that recruit regenerative cells to the site of injury. Genetic and pharmacological inhibition of signalling pathways will be used to identify key
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the implementation and ongoing review of programme level approach in the School and contributing to the strategic development of the portfolio. This will involve coordinating high quality and consistent programme and
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, with genetic approaches and CRISPR/Cas9 technologies. We are looking for a motivated applicant with a PhD (or have equivalent postdoctoral level work experience) in areas relevant to cell/development and
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Investigation of the biological behaviour and genetic regulation of rare cancers, to develop new therapies.
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Neuro-Symbolic Methods for Explanation-Based Reasoning with Large Language Models