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relating to Biomedical Sciences or Neuroscience. MRes in a relevant discipline is advantageous. Applicants whose first language is not English require an IELTS score of 6.5 overall with a minimum of 5.5 in
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Institute of Photonic Technologies to be undertaken within the College of Engineering and Physical Sciences at Aston University. Financial Support This studentship includes a bursary to cover the fees rate
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control. Joining the leading researchers in the Centre for Engineering Research at the University of Hertfordshire, collaborating with our industrial partners and becoming a member of the vibrant doctoral
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Overview: As data becomes more accessible, new challenges arise around how best to use it—especially in complex, multi-system environments like aerospace. Ontologies offer a powerful solution by
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this testbed available to users for testing hardware and applications. NPL will lead on the testing and security evaluation of the testbed and collaborate widely on the technology development. The student’s
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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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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
. This PhD project will tackle that challenge by developing intelligent methods that combine AI techniques such as language models that interpret technical text and knowledge graphs that map engineering
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to how well they meet the following criteria: A first class or strong upper second-class undergraduate honours degree in Engineering, Mathematics, Computer Science or Physics Excellent English written and
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part of the Sports Technology Institute with a long history of successful research collaborations with global companies and Loughborough University is currently ranked the best university in the world
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
intelligent methods that integrate large language models (LLMs) and knowledge graphs to interpret technical documentation and structure complex engineering knowledge. The goal is to create digital twins