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multiple aspects of work to meet deadlines. You will adapt existing and develop new scientific techniques and experimental methods, as well as contribute ideas for new research projects. You will use
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University Department of Psychiatry, clinical institutions such as Cambridgeshire and Peterborough NHS Foundation Trust, and with a secondment to industry (Akrivia Health) to advance science and develop common
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submit a statement of interest describing your previous experiences that shaped your scientific interests and how you plan to use this opportunity to advance your own career, as well as contributions
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scientific breakthroughs. The successful candidate will lead research on ERC PoC project PepVerse within Prof. Knowles' research group at the Yusuf Hamied Department of Chemistry at the University of Cambridge
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experiences that shaped your scientific interests and how you plan to use this opportunity to advance your own career, as well as contributions to the scientific community that demonstrate good citizenship
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) programme . This is a fixed term position until March 2026. About STARSand HSMA and the work you will be involved with. STARS is an Open Science project that aims to increase the quantity and quality
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Postdoctoral Research Associate in Forest Resilience, Climate Change, and Human Health in the Amazon
, epidemiology, and socio-environmental modelling. To be considered a successful candidate; A PhD degree in Ecology, Biodiversity analyses, Environmental Science, Remote Sensing, Epidemiology, Data Science, or a
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University Department of Psychiatry, clinical institutions such as Cambridgeshire and Peterborough NHS Foundation Trust, and with a secondment to industry (Akrivia Health) to advance science and develop common
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December 2027 . The Department of Physics at Swansea University is seeking to appoint a Postdoctoral Research Associate (PDRA) in Semiconductor Physics and Terahertz Science and Technology. The successful
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About the Role We are seeking a researcher for a new programme focused on improving understanding of cancer risk and developing novel multicancer risk prediction models to support cancer prevention