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The job information is shown below. Please click on the links to see full details. The Learning Development teams will collaborate with academic and other professional services staff to design and
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-efficiency trade-offs, using automated configuration to find Pareto-optimal designs under real deployment constraints. 2) Build the distributed learning loop. Develop the learning and update mechanisms
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collaboration across disciplines, strengthens partnerships with industry and society, and nurtures a thriving global network, who spearheads advancements in AI & Machine Learning, Data Science, Environmental
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to Lancaster's high-performance computing facilities. Essential Requirements PhD in Machine Learning, Computer Science, Computational Neuroscience, or related field Demonstrable experience developing deep learning
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from working closely with its team of post-docs, associated researchers and partners (that range from Microsoft Research to the NHS). For this project you should have a strong interest in AI/Machine
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, using signal processing/machine learning techniques, to realise all-weather perception in autonomous vehicles with high-quality multiple-input-multiple-output (MIMO) radar sensing/imaging. The project
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PhD studentship in Machine Learning-Based MIMO Radar Sensing for All-Weather Perception in Autonomous Vehicles Award Summary 100% fees covered, and a minimum tax-free annual living allowance
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-informed machine learning (PIML) with domain-specific engineering knowledge. By embedding physical laws and corrosion mechanisms into data-driven models, the research will produce more accurate
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Supervisor: Professor Fernanda Duarte Start date: 1st October 2026 Applications are invited for a fully-funded DPhil studentship in Machine Learning Interatomic Potentials for Metal-Ligand
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Digitalising populations of structural systems using machine learning (S3.5-MAC-Dardeno) School of Mechanical, Aerospace and Civil Engineering PhD Research Project Competition Funded Students