10 structural-engineering "https:" "https:" "https:" "https:" "Universidade do Minho CTAC" positions at Oxford Brookes University
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Faculty of Health, Science and Technology 3 Year, full-time PhD studentship Eligibility: Home UK/EU and International applicants Bursary p.a: The stipend is at the UKRI rate (currently £20,780
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Faculty of Health, Science and Technology 3 Year, full-time PhD studentship Eligibility: Home UK/EU and International applicants Bursary p.a: The stipend is at the UKRI rate (currently £20,780
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the 'Apply for Job' button to complete the recruitment form. N.B. Please do not click on the 'Apply for Job' button if you have not been invited to do so. https://my.corehr.com/pls/oburecruit
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. For more information on our benefits package, please visit https://www.brookes.ac.uk/staff/working-at-brookes/benefits At Oxford Brookes, inclusivity is one of our five guiding principles: we take positive
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an additional £2000) University fees and bench fees: The studentship covers bench fees, stipend, and tuition fees. Visa and associated costs are not funded. International applicants can visit https
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, please click on the 'Apply for Job' button to complete the recruitment form. Please ensure you use a personal email address to register and apply rather than a Brookes affiliated one. https://my.corehr.com
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Variable Hours employee, please click on the 'Apply for Job' button to complete the recruitment form. N.B. Please do not click on the 'Apply for Job' button if you have not been invited to do so. https
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on buildings and carpentry elements ● Identify defects and report clearly to the Buildings Team Supervisor Teamwork & Support ● Work closely with other technicians, engineers and external contractors
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pre-registration programmes at BSc and MSc degree levels, located within the School of Sport, Nutrition and Allied Health Professions (SNAHP) in the Faculty of Health, Science, and Technology (HST). We
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: At least an upper second-class degree (preferably MSc) in a Science or Technology discipline. Good working knowledge of machine learning and deep learning. Hands-on knowledge of Python or PyTorch