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Field
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: Applying robust bioinformatic and statistical methods to detect, authenticate, and analyse ancient pathogen DNA from large-scale ancient metagenomic shotgun sequencing datasets. Performing evolutionary
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public health. In this role, you will develop and evaluate novel AI and machine learning methods using large-scale multimodal datasets, contributing to epidemiology-informed foundation models, predictive
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through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Lithosphere-scale processes control
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. This line of research is explicitly focused on the identification of large-scale macroecological patterns using established and innovative statistical modelling approaches. Beyond this research focus
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representation in atmospheric prediction models. The initial appointment is for a term of one year but may be extended upon satisfactory performance and available funding. Job description: Using large-eddy
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About the lab The Laboratory of Causal Systems Immunology combines causal inference, probabilistic AI and large-scale in vivo perturbation experiments to uncover how genes shape immune-cell states
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of research investigating cancer risk and prevention. The appointee will work closely with Professor Ruth Travis, Dr Karl Smith-Byrne and other members of the research team, using large-scale epidemiological
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design, train and implement ARCA: an AI foundation model for crop microbiomes. You will work at the interface of deep learning, bioinformatics and microbial ecology, using large-scale microbiome and genome
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MLIPs and DFT workflows (e.g., VASP, atomate2). Experience running and scaling simulations on HPC. Broad knowledge of solid-state materials science. Ability to work independently within a large multi
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and spatial analysis techniques to large-scale spatial transcriptomics and imaging datasets, using tools such as MuSpAn to identify spatial biomarkers and uncover the biological mechanisms driving