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or image analysis. The post is full time and fixed term until 30 June 2028. The closing date for applications is noon UK time on Friday, 11 July 2025 You will be required to upload a CV and Supporting
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for the early detection of mild cognitive impairment (MCI) and prediction of its progression to Alzheimer¿s disease through the analysis of corneal nerve images. You will be based in the Institute of Life Course
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are: development of in vivo imaging assays for understanding efficacy of novel antifungal drugs, assay development, determination of resistance liabilities of novel antifungal drugs, via both in vitro and in vivo
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using a range of methods including cutting-edge single cell and imaging techniques. Ultimately this information will provide fundamental insights into human biology and may in the future lead to improved
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exploiting cutting-edge mechanobiological, as well as imaging approaches2-5 with the aim to investigate the role of mechanical sensing and memory in cardiovascular disease. The postholder of this British Heart
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-Watt have a long–standing track record in researching ground-breaking single photon detection and applications in quantum communications and single-photon imaging. With single-photon avalanche diode
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culture, astrocyte co-cultures, gene editing, lipidomics, ICC/IF, confocal imaging, and electrophysiology. Equality, Diversity & Inclusion The University is committed to supporting and promoting equality
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computational design and adaptive landscape and territorial systems. ADAPT PhD researcher, focusing on environmental data analysis and prototype development. International partners at ETH Zurich, MIT Media Lab
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drugs. Areas of interest are: development of in vivo imaging assays for understanding efficacy of novel antifungal drugs, assay development, and determination of resistance liabilities of novel antifungal
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of virus evolution into mathematical models of spillover infection and transmission of prototype viruses representing viral families concern to support the development of methods for virus sequence analysis