23 design-"https:"-"https:"-"https:"-"Vilnius-University" PhD positions at The University of Manchester
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hydrodynamics is therefore critical to the effective design and operation of future commercial farms. The interaction between surface gravity waves and tidal stream turbines is a critical design load condition
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to be exploited by design. Working with reactions where catalyst choice leads to fundamentally different products, and where mixed solvent systems produce synergistic effects that are not fully explained
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engineering and synthetic biology, accelerating innovation across sections including pharmaceuticals, agri-tech and clean manufacturing. Students will undertake interdisciplinary, co-supervised projects across
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Department: Materials Title: Designing polymer drug delivery implants with tuneable release pathways Application deadline: 11/03/2026 How to apply: Click the 'Apply' button above. This 3.5-year PhD
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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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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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in porous geological formations. The successful candidate will develop and implement computational models, validate them against experimental or field data where available, and contribute to the design
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performance. This PhD project aims to develop a data-driven framework for graphene aerogel design by integrating structured experimental Design of Experiments (DoE) with machine learning (ML). The student will
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experience combined compression, tension, and shear while simultaneously undergoing severe thermal gradients. Yet most current material models and design approaches are based on simplified stress states and
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systems and simplify plant operation and maintenance. However, credible assessment and rapid design iteration require modelling approaches that can efficiently capture the strong coupling between neutronics