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required for the role can be found within the Job Description here If you would like to discuss the application or recruitment process before making an application, please contact Sam Rafferty at Resourcing
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and Registration process: SST supports the Registry and Academic teams throughout the registration and induction procedures to maintain a close relationship with the students and keep pertinent data
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photodetectors. This studentship presents a unique opportunity to be at the forefront of quantum simulation technology and contribute to the future of semiconductor devices. If you hold a degree in physics
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photodetectors. This studentship presents a unique opportunity to be at the forefront of quantum simulation technology and contribute to the future of semiconductor devices. If you hold a degree in physics
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level in a discipline related to Engineering, Physics, Mathematics or Computer Science and have obtained or about to obtain a PhD in the same area with application to deep learning. You will have
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and machines for physical lab-scale experiments, the researcher should be familiar with testbench setup (e.g., battery emulator and inverter/converter) and machine tests. Relevant experiences will be
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for a passionate candidate excited about the latest developments in technology. You will work in a multidisciplinary, motivating, and supportive environment. You will need a background in physics
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that are considered unattainable. The ideal candidate will have a solid background in deep learning methods and an understanding of solid state physics, and particularly the thermodynamics of alloys. The work will be
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premixed and non-premixed regimes is the presence of intrinsic flame instabilities (IFIs) that affect flame dynamics, and heat release. Currently, we lack physics-based predictive or data-driven models able
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regulation in stress resistance and ageing, identifying novel roles played by PrLPs and lysosomes in the ageing process and in anti-ageing interventions. These insights may ultimately lead to the