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criteria for the role, outlining in particular previous experience in fields relevant to the project, such as bibliography, book history, Digital Humanities, and Victorian studies, and (b) gives a brief
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well as undergraduates and program alumni. The position requires working with sensitive materials in a deadline-driven, high volume, and fast-paced environment. Responsibilities Assist and support IIP Director and team in
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details can be found at https://www.net-zero-fibe-cdt.eng.cam.ac.uk/ The project is funded in collaboration with Ramboll and Buro Happold who work across diverse projects with key clients focused
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of experimental data - Molecular Dynamics and Finite Element calculations. . Metallic nanoparticles (NPs) exhibit unique physico-chemical properties departing from those of bulk materials, primarily due
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
expression in essays, creative pieces, even emerging forms of digital media. ECL is home to the undergraduate and graduate programs in English and the undergraduate and graduate programs in Comparative
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Computer science » Digital systems Computer science » Programming Computer science » Systems design Mathematics » Algorithms Mathematics » Statistics Researcher Profile Recognised Researcher (R2) Country Belgium
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. Project description We are currently extending our team working on the MADE REACT project which focus on challenges within the design of robot solution for resilient high-mix low-volume manufacturing
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equipment. Calibrate field equipment to ensure accurate application of fertilizers and pesticides. Responsible for the operation, maintenance, and repair of high-volume, in-ground irrigation system, and
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. This is a key leadership role responsible for ensuring our students receive high-quality, consistent and timely advice across all channels in a fast-paced, high-volume environment. You will lead a dedicated
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environments Practical experience with machine learning and AI methods and an interest to learn, adapt and apply ML methods to challenging problems in mass spectrometry. Independent and cooperative working in