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Theoretical Quantum Materials We invite applications for a PhD position in theory of quantum materials at Aalto University, Department of Applied Physics. The position is part of the FUN-VAN Research Council
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
Overview: Cranfield University invites applications for a fully funded 3-year PhD, supported by the EPSRC DTP and Rolls-Royce. This studentship covers tuition, a tax-free stipend, funding
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Award Summary 100% home tuition fees and £20,780 annual stipend (25/26). International candidates must cover the fee difference. Overview We invite applications for a fully funded PhD at Newcastle
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the development of globally inclusive language technologies and to design transformative approaches to overcome them. Responsibilities of the post holders include the development of new methods for multilingual
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funding restrictions, this is only available to those eligible for UK fees. How to apply: All applications should be made online . Under programme name, select School of Sport Exercise and Health Sciences
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degree which includes a substantial research element, with a score of 65% or above in the taught modules and 65% or above in the dissertation. Complete the PhD Programme online application . Your
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degree which includes a substantial research element, with a score of 65% or above in the taught modules and 65% or above in the dissertation. Complete the PhD Programme online application . Your
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study: search for the ‘Course Title’ using the programme code: 8020F select ‘PhD Biology (full-time)' as the programme of study You will then need to provide the following information in ‘Further Details
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This PhD focuses on the development of a novel approach to measuring the traction behaviour of artificial turf, supported by FieldTurf, a global leader in the production of artificial turf for sport
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an increasingly complex development environment. Areas to consider that impact the modelling are: Framework Language Process How wide / how deep i.e. what do we model and why? How much provides a good answer i.e