490 computational-physics-"https:"-"https:"-"https:"-"https:"-"University-of-Minho" PhD positions in United Kingdom
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high 2:1 in computer science, mechanical engineering, or aerospace engineering. You should have programming experience applied to physics/engineering problems and/or experience with machine learning and
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First or strong Upper Second-class honours degree (2:1 with 65% average), or international equivalent, in Engineering, Computer Science, Physics, Mathematics, or a related discipline, and demonstrate
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. Patrick Degenaar Eligibility Criteria We are adopting a contextual admissions process. This means we will consider other key competencies and experience alongside your academic qualifications. An example
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the future of energy for homes in the UK. Aim You will have the opportunity develop an innovative EMS design solves existing challenges. This new architecture will reduce costs, minimise physical footprint
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-motivated candidate with a 1st or high 2:1 degree in Engineering or Physical Sciences or a related science discipline. Prior experience in thin-film deposition, microscopy, spectroscopy, electronics
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, synthesise and test the compounds. Using traditional methods, the equivalent process would take months. These approaches will be applied to optimisation of drug candidates for selected cancer targets
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap
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of first or second class UK honours degree or equivalent in a related discipline, science (chemistry/physics) or engineering. The ideal candidate should have some understanding in the area of materials
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for feedstock characterization. 1st or a 2:1 in a Chemical Engineering, Mechanical Engineering, Materials Engineering, Chemistry, Physics If you are interested in this project, please send your CV and cover
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multidisciplinary effort to investigate the anatomical, physical and cellular factors that shape internal root environments. The project will explore how root organisation and environmental conditions combine