417 cloud-computing-"https:"-"https:"-"https:"-"https:"-"https:"-"UCL"-"UCL" PhD positions in United Kingdom
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PhD Studentship: Bottom-up Decoding of Protein Conformational Landscapes: from Gas-phase to Solution
) at the University of Warwick is an innovative, interdisciplinary fully funded PhD programme that brings together science, engineering, and mathematics to tackle some of the most pressing challenges of our time. Big
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for Real‑World Impact HetSys (Centre for Doctoral Training in Modelling of Heterogeneous Systems) at the University of Warwick is an innovative, interdisciplinary fully funded PhD programme that brings
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that will consider the electromagnetic aspects, through computer modelling and simulation, and then identify material systems that enable the design and manufacture of antennas for test and characterisation
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Systems) at the University of Warwick is an innovative, interdisciplinary fully funded PhD programme that brings together science, engineering, and mathematics to tackle some of the most pressing challenges
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. Diversity and Inclusion at Cranfield We are committed to fostering equity, diversity, and inclusion in our CDT program, and warmly encourage applications from students of all backgrounds, including those from
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requirements A minimum of a 2:1 first degree in a relevant discipline/subject area (e.g. aerospace, automotive, mechanical, electrical, chemical, computing, and manufacturing) with a minimum 60% mark in
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undergraduate degree (or international equivalent) in Engineering, Industrial Engineering, Manufacturing Engineering, Systems Engineering, Operations Management, Computer Science, or a related field. A master's
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. This PhD project will address these critical gaps through an ambitious translational research programme combining human studies with cutting-edge laboratory science. The student will design and lead a
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complexity and surface roughness, using computational methods like physical optics and the discrete dipole approximation. Supervisors Entry requirements Applications are invited from individuals with a
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, this enables the development of more accurate computational models for various industrial processes. The experimental methods developed in this project will directly contribute to a better understanding of