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PhD Studentship: Dissecting the Molecular Architecture and Function of LMTK3 as a Therapeutic Target
protein, including the interplay between its domains and its diverse, non-canonical functions, remains elusive. This project will build directly upon Professor Giamas's findings to dissect the molecular
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which is £5,006 for the year 2025/26. International students will need to make up the difference in fees (band 2, £22,500 for the year 2025/26). The student will receive a standard stipend payment for
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for cardiovascular applications. You will build on our group’s expertise on Physics-Informed Machine Learning (PIML), a powerful approach that combines data-driven AI with the rigour of physical and physiological
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of Europe’s leading academic departments of population health sciences. The post will suit researchers interested in understanding computers energy usage to improve carbon footprint monitoring and reduce the
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of Computational Solid Dynamics Building upon very recent work made by the supervisory team, this FULLY FUNDED 4-year PhD project will investigate challenging aspects such as: (1) exploration of a truly “n” multi
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Supervisors: Dr Christopher Wood (Faculty of Engineering) and Dr Grazziela Figueredo (School of Computer Science) External Partner: Build Test Solutions Ltd (BTS) Start Date: 1st October 2025
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. The research has the potential to make a significant and novel contribution to player-surface traction and support the development of new testing capabilities relevant to manufacturers of both artificial turf
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marine applications. The successful candidate will work closely with multidisciplinary teams spanning mechanical, electrical, and marine engineering, contributing to the advancement of clean energy
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LSE is committed to building a diverse, equitable and truly inclusive university Salary from £36,008 to £40,991 pa inclusive with potential to progress to £43,854 pa inclusive of London allowance
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for cardiovascular applications. You will build on our group’s expertise on Physics-Informed Machine Learning (PIML), a powerful approach that combines data-driven AI with the rigour of physical and physiological