599 computer "https:" "https:" "https:" "https:" "Robert Gordon University" PhD positions in United Kingdom
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, robotics, and machine learning. You will work within a multidisciplinary supervisory team spanning engineering, robotics, and computer science, and collaborate with researchers working on real-world
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clinically meaningful explanations. Finally, the project will develop new evaluation frameworks to assess reasoning quality, robustness, computational efficiency, and real-world clinical usefulness, supporting
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numerical simulation is desirable. Experience with computational tools such as ANSYS Fluent, STAR-CCM+, or COMSOL Multiphysics would be advantageous. Good oral and written communication skills with
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Advances in computing, experiments, and information will continue to reshape engineering in the next decade. This PhD position will nurture a multidisciplinary innovator with the tools to unravel
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researcher? Do you want to be trained in cutting-edge experimental and computational techniques to understand how clot contraction influences thrombus stability and embolism risk? Are you excited to be part of
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. The successful candidate will work closely with the project sponsors to deliver the outputs and will have access to a bespoke training programme. This project will deliver a model that integrates water quality to
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one of the world’s leading centres for additive manufacturing research and development, invites applications for a fully funded PhD programme. Metal additive manufacturing is transforming how complex
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supervision from an experienced team spanning Manchester Met and Chester Zoo. You will benefit from a skills training programme through our Doctoral College, and will be based in the Faculty of Science and
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of £20,780 (2025/26 UKRI rate). An additional allowance will be provided to contribute towards consumables, equipment, and travel related to the project. Overview ReNU+ is a unique and ambitious programme
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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