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echocardiography dataset called CAIFE consisting of both healthy and abnormal fetal heart scans. You will be responsible for the design and testing of original machine-learning based methods for fetal heart
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and numerical methods for many-body dynamics beyond the reach of standard classical simulation. About the role We have a high preference for a candidates who is willing to start imminently, and before
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administer a benchmark for auto-formalization of mathematics, and to engage in related research. Duties will include contributing to the benchmarking dataset, organizing and ensuring the quality of the data
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initiative involving leading photon science facilities, MAX IV is developing sustainable approaches to scientific data reduction and scientifically validated lossy-compression methods for tomography and
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to advance the development and application of reliable, interpretable and uncertainty-aware machine learning methods for high-stakes regulated domains, including law, finance, policy and regulatory decision
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(NC). In the project, we aim to establish a reliable analysis package for nitrocellulose. Your role is to develop and validate methods for the key properties of NC – including degree of substitution
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up and maintain experimental workflows by implementing or adapting existing tools. Methods will include advanced flow cytometry, in vitro functional assays for hematopoietic stem cells and immune cells
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, Kupffer cells) • Characterise the reconstructed tissue: biologically, mechanically and functionally, using the laboratory's various methods or other specialist expertise. • Study the response of the liver
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the dissertation, must be completed by the date of appointment. Demonstrated research experience with density functional theory or closely related first-principles atomistic simulation methods. Demonstrated research
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, Genetics, Genomics, Bioengineering, Molecular Biology, or a related field. Strong expertise in molecular biology and functional genomics methods relevant to neural systems. Experience with CRISPR-based