365 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" PhD positions in United Kingdom
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Application deadline: 31/03/2026 Research theme: Biocatalysis and Protein Engineering Centre for Sustainable Synthesis – BioProcess How to apply: https://www.mib.manchester.ac.uk/research/centres
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SWAN Charter recognises commitment to advancing gender equality in Science, Technology, Engineering, Maths and Medicine (STEMM) employment in academia. https://www.gla.ac.uk/schools/bohvm/athenaswan
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-funded Fees and Bench fees: Bench fees £1500 Information on fees can be found here: https://www.brookes.ac.uk/study/fees/postgraduate-research-fees/ Start Date: September 2026 Project Title: Dietetic Needs
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. What you should have: A 1st degree in physics or engineering. An interest in optics, some ability in computer programming A desire to learn new skills in complementary disciplines. You will work jointly
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project experience is also welcomed. For more information on the entry requirements and fees please visit our website. https://www.kcl.ac.uk/study/postgraduate-research/areas/cancer-and-pharmaceutical
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above and our ‘Find a Supervisor’ page for information on our academic staff and their research interests. For guidance on writing a research proposal, please see: https://www.westminster.ac.uk/study
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. Funding: Full coverage of tuition fees and an annual tax-free stipend of £22,780 for Home, EU and International students. Find out more about fee status at: https://www.imperial.ac.uk/study/pg/fees-and
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status at: https://www.imperial.ac.uk/study/pg/fees-and-funding/tuition-fees/fee-status/ . Eligibility: Due to the competitive nature of our studentships, candidates will be expected to achieve/have
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Fibre reinforced composites have excellent in plane strength and stiffness and are being used in increasing quantities in aerospace, sports, automotive and wind turbine blade industries. However fibre reinforced composites are weak in their through thickness direction. This weakness can result...
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for representing and combining multimodal information over time. Grounded in machine learning, representation learning, and efficient algorithms, the work addresses real-world challenges in sustainable and