471 evolution "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "University of St" uni jobs at University of Sheffield
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administration support to ensure the effective running and development of the products. This may include enabling functionality, handling permissions and managing users. Support the implementation and maintenance
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application portal for postgraduate research in Chemistry: https://www.sheffield.ac.uk/postgraduate/phd/apply When completing your application, please specify Dr Marco Conte as the proposed supervisor and
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-term for 24 months Line manager Professor Cooper-Knock Direct reports N/A Our website https://sheffield.ac.uk/smph For informal enquiries about this job contact smph-west-staffing@sheffield.ac.uk Next
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2026 - 31st August 2027 Line manager Research Fellow Direct reports N/A Our website https://sheffield.ac.uk/mps For informal enquiries about this job contact Cheuk Yu Mak, Research Fellow on C.Mak
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Crowther, Dr R Parker Application Deadline: 31 January 2026 Details Massive stars are rare, but nevertheless influence the evolution of galaxies through their mechanical, chemical and radiative feedback
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, and a competitive living stipend. First class or upper second 2(i) in a relevant subject. To formally apply for a PhD, you must complete the University's application form using the following link: https
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of the technique and unlock new areas of materials exploration. The project will involve a mixture of coding, data curation, practical experiments at UK national X-ray and Neutron facilities, and method development
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, these experiences will enhance both professional development and the overall PhD journey. Your role as a PhD researcher: As a PhD researcher, you will work at the intersection of engineering, biology, and materials
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Direct reports Support Technician Our website https://sheffield.ac.uk/mac For informal enquiries about this job contact Phillip Pickstock, School Technical Manager: on p.pickstock@sheffield.ac.uk Next
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Development and Validation of a Multimodal Wearable Headband for Objective Bruxism Monitoring Using Machine Learning (S3.5-DEN-Boissonade) School of Clinical Dentistry PhD Research Project