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deployment, ensuring that all deliverables meet high standards of performance, scalability, and user experience. This is an exciting, dynamic position offering the chance to engage with cutting-edge
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to excellence will help us create high-performance optical components that advance our research goals and commercial partnerships. Who We’re Looking For We seek a talented research fellow with skills and
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, to satisfy end-user requirements for performance, size, weight, power and cost. You can expect to see your outputs integrated and used in real-world high Technology Readiness Level systems across a range of
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industry partners on research projects to reduce battery cost, weight, and volume; to improve performance and reliability (faraday.ac.uk ). The overall aim of the ReLiB project (https://relib.ac.uk/ ) is to
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bring together scientists and industry partners on research projects to reduce battery cost, weight, and volume; to improve performance and reliability (faraday.ac.uk ). The overall aim of the ReLiB project (https
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(https://www.cam.ac.uk/research/research-at-cambridge/strategic-research-initiatives-networks ). The School of Biological Sciences has state of the art facilities in imaging, high performance computing and
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, bioinformatics or related discipline Strong computational skills, with expertise in scripting in BASH and either R or Python Experience with analysing complex datasets on high-performance compute clusters A track
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(HPB). The medical oncology grouping sees close to 550 new cases of these cancers a year. There is a large active clinical trials programme that spans phase 1 to phase 3. These patients have a poor
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performance computing, and engineering software development are also of interest. Proven track record of publishing high-quality journals is required for the Research Fellow position. Ability to communicate
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Supervised Machine Learning and Reinforcement Learning. The objective is to significantly enhance battery performance and longevity. While conventional methods rely on either physics-based models or high-level