296 distributed-computing-"St"-"Washington-University-in-St"-"St" positions at University of Sheffield
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Data Driven Modelling, Machine Learning, Applied Mathematics/ Statistics, or related engineering and computing fields (or have equivalent experience) Essential Application Strong background in data
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Materials at Sheffield (SMASH) research team in the School of Chemical, Materials, and Biological Engineering. This project constitutes part of the 5-year BuildZero programme , a £6 million project funded by
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Interplay between Algorithms and Combinatorics School of Computer Science PhD Research Project Directly Funded Students Worldwide Prof Parinya Chalermsook Application Deadline: 31 July 2025 Details
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data provision within the School. The postholder manages the administrative and reporting functions for all Triple Crown and programme accreditations, keeping abreast of changing standards and
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, programme and budget. · Carrying out maintenance project works, identifying the requirements of departments and preparing a design brief. Preparing designs for minor works including specification and
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ideal opportunity to join international research programme bridging across disciplines between soil science, analytical chemistry, and geobiology. The post will contribute to the strategic goals
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preferences for them using birds as a model system. Capitalising on recent advances in computational neuroscience and machine learning, specific objectives are to (1) quantify common design features of avian
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Overview Our postgraduate research student community plays a central role in the research life of the University. PGR students undertake their own programme of research, supervised by an academic
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delivery of student experience as students progress through their programme journeys, from welcome and transition to graduation. You will set the annual schedule of key activities and lead developments to
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of agricultural weeds to herbicdes from an eco-evolutionary perspective. This project will develop models for the evolution of herbicide resistance that combines field data and computer models. The aim is to