14 computational-physics "https:" "https:" "https:" "https:" "IFM" Fellowship research jobs at University of Leeds
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degree (or have submitted your thesis before taking up the role) and research experience in Physics and/or Engineering along with significant experience in experimental liquid crystal physics, including
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discussing flexible working arrangements. Would you like to be part of a major collaborative research programme to help tackle transport’s contribution to the climate crisis? Are you looking to apply your
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online process analytical technology (PAT), embedding sustainability metrics into the optimisation loop, and apply transfer learning to accelerate the transition from batch to continuous flow processes
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visa. For more information please visit: https://www.gov.uk/global-talent To explore the post further or for any queries you may have, please contact: Professor David Meads; email: D.Meads@leeds.ac.uk
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on the costs of delivery of safely managed urban sanitation services (https://cactuscosting.com/ ). We are looking for a Senior Research Fellow to join our team and lead the development of the next phase of
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/skilled-worker-visa For research and academic posts, we will consider eligibility under the Global Talent visa. For more information please visit: https://www.gov.uk/global-talent If you are looking for a
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tailored to your career goals. You will have, or be close to obtaining, a PhD in deep learning, computational geosciences, computer sciences, mathematics, or physics, and have experience of developing and
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core team. To increase integration with the UKESM team, while this is a University of Leeds position, the successful candidate will be physically based at the Met Office in Exeter, where the bulk
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-intensive Universities? As a Research Fellow in Computational Climate Politics you will work on the UKRI FLF project “Understanding normative change to address the climate emergency ”. This is a 4+3 grant
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the School of Mechanical Engineering. The project is part of a new £7M EPSRC funded Programme Grant that brings together a team of researchers from the universities of Leeds, Durham and Manchester