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We are looking for a motivated and talented postdoctoral-level researcher with experience in executable modelling to join a cutting-edge project developing Digital Twins for rare diseases. This is a
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CRISPR tools to correct or model the defective genomic DNA, and further deliver these newly-engineered editors into targeted organs to correct the corresponding phenotypes. The current disease models
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targets and biomarkers. Study cardiomyopathy across models of diabetes, cancer, and pressure overload. Collaborate in an interdisciplinary team and contribute to high-impact publications. Your
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, machine learning, mathematical modelling, or a related field, to join our research team in the Department of Applied Health Sciences. The successful candidate will work on an NIHR funded methodology project
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development and regeneration. Our research combines in vivo genetic models, in vitro organoid systems, advanced imaging, and high-dimensional sequencing approaches to uncover fundamental principles by which
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, molecular immunology, and translational models. Led by Dr. William Gibson, the lab is based at Dana-Farber and Harvard Medical School and is committed to developing new therapeutic platforms that bridge
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leveraged to accelerate learning from both classical and quantum data. The project will develop rigorous theoretical frameworks to understand key properties of quantum machine learning models—expressivity
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German Center for Diabetes Research (DZD) and the TransCampus collaboration with King's College London. We analyze large clinical cohorts and experimental models to unravel disease mechanisms and identify
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can successfully predict previously-unknown regulators of seed development through functional genetic analysis of conserved, uncharacterised genes in the model seed plant Arabidopsis thaliana
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development and implications in neurodevelopmental disorders. Using Drosophila , mouse models, and human brain organoids, our work is at the forefront of neuroscience research, with recent publications in PNAS