11 evolution-"https:" "https:" "https:" Postdoctoral positions at University of Oxford
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on carbon emissions reduction and network telemetry. You will contribute to the development of a framework that reduces the carbon emissions of networks through the use of carbon-aware network
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at the University of Oxford. This is an exciting opportunity to work with world-leading researchers and contribute to the development of innovative new approaches to combat antimicrobial resistance, which is a
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developing a screening tool to support clinical evaluation for psychosis risk, powered by generative artificial intelligence. You will particularly support the development of a novel research method for
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for students, line-manage Research Assistants and D.Phil. students, mentor on methods, analysis and career development About You You will hold a Ph.D/D.Phil in a quantitative or theoretical discipline (e.g
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on the research activity of the lab is available at: https://www.rinaldi-lab.com/ . The successful candidate will be involved with study design and experimental conduct. The post holder will work at the newly built
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research, contribute intellectually to programme development, and ensure outputs are robust, reproducible, and positioned to inform translational and therapeutic advancement. The position requires strong wet
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, characterize their growth and key parameters, and track their evolution and spatial spread? This post is full time and fixed-term until 31 December 2027. Prior work on the topic from our team is available
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-development of new study protocols. About You You will have or be close to the completion of a relevant PhD/DPhil e.g., neuroscience, together with relevant advanced analysis experience. Sufficient specialist
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The University of Oxford offers a comprehensive range of competitive benefits available to all members of staff designed to support both professional and personal wellbeing (https://unioxfordnexus.sharepoint.com
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. Information on the research activity of the lab is available at: https://www.rinaldi-lab.com/. The successful candidate will be involved with all aspects of the data analysis including design, experimental