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the ranking. However, STV method becomes considerably more complex with encrypted ballots. Our goal is to develop an algorithm/protocol to count encrypted ballots using the STV method. Our first point of
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hybrid discretisation frameworks that apply varying fidelity across the computational domain. This includes creating conservative transmission algorithms that ensure consistent exchange of information
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industrial adoption of high-order CFD technologies. As the PhD researcher on this project, you will investigate and develop the numerical and algorithmic components needed to make this hybrid high order to low
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, you will develop the numerical, geometric and algorithmic techniques needed to generate reliable high order meshes for complex, multiscale industrial geometries. You will work within a technically
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. Based at Swansea University, you will play a central part in a multi-institution effort that blends algorithmic innovation with robust, production-quality research software. You will lead the design
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2027 working full-time. We are seeking a skilled researcher to join the Suicide Prevention & Mental Health (SPMH) team at Swansea University, led by Prof. Ann John. This position offers an exceptional
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of Prof. Mokarram Hossain and Prof. Ian Masters at Swansea University and the Industry Partner Checkmateflex. The team is further strongly supported by a few Industry partners such as Wave Venture Ltd
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harness advanced techniques such as machine learning, optimization algorithms, and sensitivity analysis to automate and enhance the mode selection process. The result will be a scalable methodology that
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/PYTHON/R/C programming • Application of Machine Learning Algorithms Additional Information Benefits This scholarship covers the full cost of tuition fees, an annual stipend at UKRI rate (currently
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within the team The appointed researcher will join the team led by Prof. Ann John with a focus on mental health and suicide and self-harm prevention. Prof. Ann John is the Swansea Principal Investigator