355 computer-programmer-"U.S"-"U"-"Embry-Riddle-Aeronautical-University"-"U.S" positions at University of Sheffield
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take place on 22nd Oct 2025. This will consist of interview and assessment task. We plan to let candidates know if they have progressed to the selection stage on the week commencing 12 Oct 2025. If you need
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year in industry as part of their engineering studies. They will support the AMRC North West low carbon team to deliver a range of research projects, commercial contracts and business support programmes
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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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goals are met Plan and manage your own workload, with guidance from colleagues as required. Carry out other duties, commensurate with the grade and remit of the post Person Specification Our diverse
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13th October 2025. This will consist of an interview and presentation. We plan to let candidates know if they have progressed to the selection stage on the week commencing 6th October 2025. If you need
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participate in any element of the recruitment process, you can contact m.potts@sheffield.ac.uk . Our vision and strategic plan We are the University of Sheffield. This is our vision: sheffield.ac.uk/vision
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the recruitment process It is anticipated that the selection process will take place mid November 2025. This will consist of Portfolio review and Interview. We plan to let candidates know if they have progressed
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of a technical activity. We plan to let candidates know if they have progressed to the selection stage on the week commencing August 2025. Contact Emma Kenny-Levick, e.l.kenny-levick@sheffield.ac.uk
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/smph For informal enquiries about this job contact Viren Ranawana at v.ranawana@sheffield.ac.uk Next steps in the recruitment process We plan to let candidates know if they have progressed
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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