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opportunity to develop skills in computational chemistry (catalyst/reagent design and mechanistic studies). The student will regularly attend organic problem classes, present their research at national
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Application deadline: 31/05/2026 Research theme: Catalysis, Synthesis, Chemistry How to apply:uom.link/pgr-apply-2425 This 3.5-year PhD project is fully funded and home students are eligible
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, computer science, or a closely related discipline (typically first-class or high 2:1, or equivalent; Master’s welcome) • Strong programming skills (for example Python, MATLAB, C/C++) • Strength in at least two of
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for translational biocatalysis, addressing critical needs in the development of sustainable biotechnologies. The programme will equip PhD students with advanced expertise in enzyme science, machine learning, enzyme
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instruments, large-scale datasets, and an international research community. Training on neutron scattering techniques will be provided. The project is ideal for students who are interested in computational
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computational enzymology to uncover mechanistic principles that guide future enzyme design. The project offers comprehensive training in biocatalysis, enzyme design and engineering, organic synthesis, structural
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workflows and contribute to building UK capability in an important advanced reactor area. The ideal candidate will enjoy computational modelling and quantitative problem‑solving, with a strong foundation in
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infrastructure. The successful candidate will benefit from access to extensive expertise across The University of Manchester in civil engineering, structural engineering, fire engineering, computational modelling
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an excellent CV are strongly encouraged to contact the supervisor to discuss their opportunities. The ideal candidate has a Master degree in chemistry, physics, chemical engineering, or material science. Solid
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skills training provided by a mixture of industry and academic project partners covering structural biology; biophysical and analytical methods; computational modelling; directed evolution; process