85 computer-science-quantum "https:" "https:" "https:" "https:" "https:" "University of Waterloo" positions at Cranfield University
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Organisation Cranfield University Faculty or Department Faculty of Engineering and Applied Sciences Based at Cranfield or Shrivenham, Oxfordshire Hours of work 37 hours per week, normally worked
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This is a self-funded PhD position to work with Dr Adnan Syed in the Surface Engineering and Precision Centre. The PhD project will focus studying high temperature corrosion mechanisms in details
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be aligned specifically to your proposed research topic and specialisms of the relevant academic staff member. Entry requirements Applicants should hold a degree within any S.T.E.A.M field (science
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Families, and sponsors of International Women in Engineering Day. We are also Disability Confident Level 1 Employers and members of the Business Disability Forum and Stonewall University Champions Programme
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Francesco Fanicchia is a recognised expert in advanced surface engineering and the development of multifunctional protective coatings, specialising in thermal barriers and fire-resistant materials. As a
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, Nuclear (CBRN), Advanced Materials for Protective Engineering: Blast and Ballistics, Advanced Imaging. Supervisors At Cranfield we place great importance on supervision and the relationship a student has
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their potential via apprenticeships. You will champion the use of technology to underpin and evidence the apprentices learning and support the journey towards successful apprenticeship completion. About You You
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Organisation Cranfield University Faculty or Department Faculty of Engineering and Applied Sciences Based at Cranfield Campus, Cranfield, Bedfordshire Hours of work 37 hours per week, normally
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Organisation Cranfield Quality Services Faculty or Department Cranfield Quality Services Based at Cranfield Campus, Cranfield, Bedfordshire Join an exceptional team at Cranfield Quality Services Ltd! We are looking for friendly people, who will bring a positive can-do attitude to work every...
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. The integration of AI into hardware not only enhances performance but also reduces energy consumption, addressing the growing demand for sustainable and efficient computing solutions. This PhD project delves