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Field
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accelerate the world’s transition to carbon-neutral energy systems? Join the Thermofluids Group in the Department of Mechanical Engineering at the University of Sheffield, and embark on a transformative PhD
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travel. Requirements: The candidate should have a 1st or high 2:1 degree in electrical/mechanical engineering, physics, mathematics, or related scientific disciplines. Skills in numerical tools and
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developing automated tools for accelerating contingency analysis is a plus. Strong analytical skills with the ability to process, interpret, and present technical results clearly. Excellent written and verbal
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for innovative research and an ideal environment to accelerate your career. We now seek a highly qualified and motivated PhD student (f/m/x) to drive the advancement and application of a novel multimodal
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for innovative research and an ideal environment to accelerate your career. We now seek a highly qualified and motivated PhD student (f/m/x) to drive the advancement and application of a novel multimodal
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methods, and self-driving laboratories to accelerate the discovery of novel materials for energy applications. You will work in a highly collaborative and interdisciplinary environment, which comprises
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: Investigate and design optimal computing and communication architectures for hardware acceleration of large-scale machine learning workloads Perform characterization and modeling of electronic and optical
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fields at a manageable computational cost. You will be exposed to surrogate (AI/ML) approaches to accelerate micro-to-macro links, as well as uncertainty quantification to account for variability in
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process here. ... (Video unable to load from YouTube. Accept cookie and refresh page to watch video, or click here to open video) About the position Digitalization and artificial intelligence (AI
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validate new capabilities within XCALibre.jl, Nottingham’s GPU-accelerated, AI-ready CFD framework, turning complex coupled physics into practical tools that engineers can use in real manufacturing workflows