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Biomedical Campus. You will join an exciting research programme investigating fundamental mechanisms of ribosome assembly, translational control and how defects in these processes drive cancer development
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colleagues. You will conduct literature reviews, develop questionnaires, conduct surveys, collect and collate data, and undertake and record the outcomes of experiments. You will manage and prioritise your own
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an original programme of research working with ecologists Dr Ashley Lyons and Dr Anne Oxbrough in collaboration with Dr Steven Ewing at the RSPB Centre for Conservation Science. This PhD is part of the Cumbria
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an original programme of research working with ecologists Dr Fay Voller , Dr Ashley Lyons and Dr Anne Oxbrough in collaboration with Dr Steven Ewing at the RSPB Centre for Conservation Science . This PhD is
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application via the University of Bristol’s online portal. Select “Management (PhD)” on the programme selection page. Candidate requirements: A first-class honours degree (or international equivalent) or strong
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should have: Undergraduate or Master’s degree in Economics or another quantitative discipline (completed by start date). Advanced programming skills in Python and either R or STATA. Willingness and ability
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experience would be an advantage. We welcome interest from applicants with a range of backgrounds. Experience with programming is vital. The ideal student will be practically minded, a fast learner, and self
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resources, and design facilities, supporting AI-powered electronics research. This project will be conducted within Cranfield’s Integrated Vehicle Health Management (IVHM) Centre, established in 2008 in
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. Safety assurance and risk management frameworks are crucial to validate AI models against rigorous safety standards, addressing potential failures and ensuring safe operations in critical environments
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of Glasgow, or University of Oxford) to undertake your PhD research. About this Project Project Title: Low-Power AI-Driven Resource Management for Enhancing Satellite Communication Link Reliability