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-year PhD studentship. The studentship will start on 1st October 2025. Project Description As Deep Learning and Generative AI applications continue to expand, optimizing computational efficiency is
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in chemical crystallography for pharmaceutically relevant molecules, on high-throughput crystallisation and single crystal X-ray crystallography (SCXRD) of linear and macrocyclic peptides. Many modern
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The ambitious roadmaps of electrification in high-performance propulsion applications are pushing the boundary of electric motor speed, especially in motorsport and aviation sectors. Achieving ultra-high speed
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of burnout or focus on individual-level solutions rather than systemic factors. This research aims to fill this gap by integrating qualitative and quantitative data to develop performance intelligence systems
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is to develop a highly innovative ‘Lab on a Bench (LoB)’ setup, integrated with Machine Learning algorithm, as a high throughput method for screening and developing formulated products that are used in
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repair and maintenance of gas turbine engines. Applicants are invited to undertake a fully funded three-year PhD programme in partnership with Rolls-Royce to address key challenges in soft robotics
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/on-wing repair and maintenance of gas turbine engines. Applicants are invited to undertake a fully funded three-year PhD programme in partnership with Rolls-Royce to address key challenges in soft robotics
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Project Link: High-throughput discovery of lysine-directed probes for protein kinases | Project Opportunities | PhD | University of Leeds Funding: School of Chemistry Studentship, in support of
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Short overview of PhD opportunity The PhD studentship aims at studying and developing more comprehensive user interfaces for computer-aided decision-making processes, which can benefit from 3D/360
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superimposed with harmonics. The other aspect is its thermal loss and dissipation significantly affect the performance of the dielectric materials. The third key aspect is the geometric structure within