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not originally designed to manage large numbers of flexible and decentralised energy resources. This PhD project will develop new AI-driven methods for operating smart distribution networks so that
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performance. This PhD project aims to develop a data-driven framework for graphene aerogel design by integrating structured experimental Design of Experiments (DoE) with machine learning (ML). The student will
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an annual tax-free stipend set at the UKRI rate (£20,780 for 2025/26) and tuition fees will be paid. Robotic metal additive manufacturing offers transformative potential for flexible, large-scale, and high
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hazardous precious metal catalysts. Delivered high-performing biocatalysts Engineered industry-ready enzymes suitable for large scale pharmaceutical manufacturing. We’ve also helped shape national policy. In
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wide range of modelling parameters, over large spatial and temporal spaces and where inputs are stochastic in nature. This is exacerbated in industrial applications that may include metals, ceramics and
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large virtual cohort of arterial flow cases and extract haemodynamic metrics and reduced-order descriptors. Use data-driven techniques of dimensionality reduction and classification (e.g. PCA, clustering
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19 Jan 2026 Job Information Organisation/Company The University of Manchester Department Computer Science Research Field Computer science Researcher Profile First Stage Researcher (R1) Positions PhD
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to: Develop automated computer aided design (CAD) and meshing pipelines to generate a library of arterial geometries representing common geometric archetypes (e.g. curved vessels, bifurcations, side branches