31 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" PhD positions at The University of Manchester in United Kingdom
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Application deadline: 30/04/2026 Research theme: Nuclear Engineering How to apply: https://uom.link/pgr-apply-2425 This 3.5-year PhD project is fully funded; home students are eligible to apply
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or search our funding database for specific scholarships, studentships and awards you may be eligible for. To apply, apply at the link: https://uom.link/pgr-apply-2425 . If you need further information
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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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Application deadline: 30/05/2026 How to apply: https://uom.link/pgr-apply-2425 This 4-year PhD studentship is open to Home (UK) applicants. The successful candidate will receive an annual tax-free
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Application deadline: 31/03/2026 Research theme: Nuclear Materials Hoe to apply: https://uom.link/pgr-apply-2425 UK only This 4-year PhD project is fully funded by the Nuclear Decommissioning
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Application deadline: 30/06/2026 Research theme: Applied Mathematics, Continuum Mechanics, Nonlinear PDEs How to apply: https://uom.link/pgr-apply-2425 UK only due to funding restrictions. The
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guest exchange (J. Am. Chem. Soc. 2025, 147, 17201 https://doi.org/10.1021/jacs.5c02868 ). It is the aim of this project to use this novel methodology to investigate a range of single crystal-to-single
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simulation results with experimental data. This project will integrate advanced AI techniques, including machine learning for parameter optimisation (e.g., Bayesian optimisation, reinforcement learning), AI
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modelling and oomph-lib for continuum mechanics simulations, enabling the integration of discrete and finite element methods. Coupled with machine learning techniques, this approach will address the complex
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industries like pharmaceuticals, food processing, and construction, the project may also incorporate machine learning methods for model calibration and optimisation, driving more sustainable material handling