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, including high throughput experimentation, programming (e.g. in LabView, Matlab) and numerical modelling. They will be joining a thriving, inclusive Chemistry department with excellent facilities
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and a construction and testing capability up to 5MW Vision This project aims to leverage the electric propulsion hardware developed in the EU-funded €40M NEWBORN – “NExt generation high poWer fuel cells
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make technological advances in more efficient and resilient manufacturing systems that can cope with demands of high value products such as electric batteries. We will also make advances towards
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of researchers who conduct cutting-edge research into NLP and AI within the University of Cambridge. Education: An excellent first degree in computer science, engineering or a closely related field Skills and
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generation high poWer fuel cells for airBORNe applications” project (https://newborn-project.eu/ ) and develop a real-time Multiphysics Digital Twin for such a system accelerating future electric propulsion
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The funding provider: Health Data Research UK Subject areas: Wider Data Science Field, Maths and Computer Science Project start dates: 1st October 2025 ** (Please see the note below regarding
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a closely related field. A strong background in quantum mechanics, solid-state physics, and computational modeling. Previous experience with density functional theory or many-body physics (beneficial
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collaborative studentship between the University of Edinburgh and the National Quantum Computing Centre (https://www.nqcc.ac.uk ). The position will be registered and hosted at the University of Edinburgh and
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quality of life to patients. However, despite the widespread clinical success of other joint replacements in the lower limb, TAR has not generally performed so well. Ankle fusion, where the bones
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Funding: Home (UK) and EU citizens who have confirmation of UK settlement or pre-settlement status under the EU Settlement Scheme The project: Acquiring high-quality footage in challenging