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include high entropy carbides, nitrides, borides, oxides, and mixed components for a variety of applications. • Assist in performing a variety of testing and analytical materials characterization using
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BCAST Applications are invited for one full-time EPSRC Industrial CASE (ICASE) PhD studentship for the project “Development of high performance and highly impurity-tolerant recycled Al alloys
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engineering, and hyperparameter tuning to produce resilient and high-performing models. · PhD in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field Strong track record
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research environment. Project background Future European power systems are expected to be driven by a very high share of renewable power plants and will be extremely complex, uncertain environments with
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, Karen, Oromo, and Somali. The supervisor for this position is Jacob Oertel, RIDGS Program Coordinator. Appointment Dates ● Fall Semester 2025 appointment dates are August 25 - January 7, 2026 ● Spring
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-2026 JANUARY 2026 start ONLY For April and October starts please use the relevant application. This form is only to be used by those self-funded applicants seeking a place on a research degree programme
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-2026 April 2026 start ONLY For January and October starts please use the relevant application. This form is only to be used by those self-funded applicants seeking a place on a research degree programme
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to produce resilient and high-performing models. · PhD in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field Strong track record of applying ML in academic or industry
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standard High School student: Regularly enrolled in a high school or participating in a home-schooling program Undergraduate and post-baccalaureate student: 6 credit hours per term Undergraduate