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chip. A strong background in the design and fabrication of silicon photonic devices, advanced characterization techniques, and an interest in semiconductor materials optimization is highly desirable
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vulnerable to hardware-level threats, including side-channel attacks, fault injections, etc., particularly when optimized for performance. This Research Fellow position focuses on AI security in the context
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chip. A strong background in the design and fabrication of silicon photonic devices, advanced characterization techniques, and an interest in semiconductor materials optimization is highly desirable
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breakwaters under varied sea conditions. 2. CFD and Finite Element Modeling Perform Computational Fluid Dynamics (CFD) simulations to optimize the design and performance of floating breakwaters. Develop finite
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medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML for turbine design and astrostatistics. These posts
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to £39,586 per annum (if PhD close to completion), and in the range of £37,337 to £44,906 per annum (if PhD obtained) The Centre for Propulsion Engineering within FEAS is looking to expand its internationally
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PhD in a relevant field (Computer Science, Mathematics are most likely to fit the role, but we are open to Chemistry, Materials Science, Chemical Engineering, etc.), expertise in cutting-edge AI and
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PhD in a relevant field (Computer Science, Mathematics are most likely to fit the role, but we are open to Chemistry, Materials Science, Chemical Engineering, etc.), expertise in cutting-edge AI and
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are included but clinical medical themes are not covered, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data
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themes are not covered, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML