16 evolution-"https:"-"https:"-"https:"-"UCL" PhD positions at The University of Manchester
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below 2 tonnes CO2e/tonne of aluminium as a supplied component and eventually to Net Zero carbon. This project is concerned with development of high strength aluminium alloys designed to provide better
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imaging. Novel data workflows will be developed to allow parallel multi-element measurements. The project is interdisciplinary, combining instrument development, analytical chemistry, laser physics and
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. The research aims to improve understanding of the geometry and extent of Late Ordovician ice sheets in the region, as well as the spatial distribution, evolution, and depositional character of ice-margin facies
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Application deadline: 08/05/2026 Research theme: "Bio-electrochemistry"; "Enzyme Cascade Evolution"; "Biosynthesis" This 3.5-year PhD project is fully funded, and UK students are eligible to apply
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, accelerating pharmaceutical development and ensuring robust product performance. Applicants should have, or expect to achieve, at least a 2.1 honours degree or a master’s (or international equivalent) in a
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track record of peer-reviewed publications may be considered for nomination to competitive scholarship schemes at the University of Manchester. This PhD project focuses on the development of advanced
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an emphasis on reaction development and optimization. Training BioProcess aims to train the next generation of bio-innovators. Our interdisciplinary programmes prepare PhD students and researchers with the real
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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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fees will be paid. We expect the stipend to increase each year. The start date is October 2026. This fully funded PhD project will merge the latest tools from experimental directed evolution with
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, stiffness loss, damage evolution, and transient creep interact under coupled loading. The project will develop temperature-dependent constitutive models informed by numerical simulation. Machine learning