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This PhD project is at the intersection of electromagnetism, numerical methods, and high-performance parallel computing, with application towards the design and optimisation of integrated circuits
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for their employability in applications. Additionally, machine learning methods need to be applicable to high-dimensional and to noisy data that are typically encountered in real-world applications. The aim of this project
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remaining functional under harsh geothermal conditions. The candidate is expected to work closely with D-TECH and may undertake a secondment period to test and apply the developed methods on industrial-scale
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associated numerical methods and AI, will be used with High Performance Computing (HPC) to improve understanding of key flow physics and inform future HPT design. Skills and Experience Required: Applicants
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, and a solid understanding of numerical analysis and familiarity with the use of analytical tools. They should also have knowledge and experience in parallel coding and spectral methods. They must have
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physics all the way to numerical simulation algorithms? Then apply now to join our team of researchers in the Quantum Information and Quantum Many-Body Physics research group. Your personal sphere
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fuels (hydrogen, methanol, ammonia), simulation tools for marine engines and/or fires due to fuel leakages, data analysis methods and their applications for ships, sufficient understanding of appropriate
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the UK Lead on participant recruitment and conduct qualitative research using participatory methods and semi-structured interviews Analyse data, contribute to co-design workshops, write reports, and
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, but current methods are not always efficient or optimal. The process lacks an intelligent, informed approach to selecting the best grinding parameters, which can lead to inefficient maintenance actions
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microbial biotechnology components into designs for a 3D bioreactor, whilst also optimising co-culturing methods and post-growth materials testing and characterisation. These materials will incorporate