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characterisation of extracellular vesicles (EVs) from a range of sources as well as high content microscopy and cardio-metabolic phenotyping in rodent models. Our main research interest is in understanding how
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and Biological Research Council (BBSRC) to investigate the biochemistry and regulatory aspects of bacterial secretion and competition systems. This post is funded for 13 months. Check out these articles
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. The study will involve the use of iPSC-based models to elucidate molecular mechanisms and biosamples from patient cohorts to validate biomarkers. As such, the post will offer an excellent opportunity
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Environment Research Council (NERC) and the Advanced Research + Innovation Agency (subject to contract negotiations), in the atmospheric chemistry-climate modelling research groups of Prof Alex Archibald, Prof
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to the advancement of AI applications in biological sciences. This role presents a unique opportunity to work with pangenomic datasets while exploring the application of Large Language Models (LLMs) and machine
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work on the development and implementation of machine learning models aimed at detecting urban drainage infrastructure components (such as stormwater drains, sewers, and manholes) from publicly available
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to chemo/radio-therapy and therapeutic/preclinical DDR inhibitors within a cohort of matched GSC heterogeneity models within the Sheffield Living Biobank of patient-derived primary glioma stem cell-like (GSC
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adaptability, strong organisation, and high expectations to everything you do. You have a solid understanding of inclusive education, the social model of disability, and how to support the personal and
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Our lab (https://www.cruk.cam.ac.uk/research-groups/biffi-group ) combines ex vivo human and murine pancreatic tumour organoid/fibroblast co-cultures with murine in vivo models and patient-derived
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with the possibility of renewal. This project addresses the high computational and energy costs of Large Language Models (LLMs) by developing more efficient training and inference methods, particularly