31 algorithm-development-"LIST"-"Meta" PhD positions at University of Cambridge in United Kingdom
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, Rust) and using standard software development and collaboration platforms (e.g. GitHub). Training for specific tasks can be provided, and the candidate will be mentored and supported in developing
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dynamics and tissue morphogenesis during embryo development using cellular, molecular and mechanical approaches. Cell movements underlie tissue patterns and shapes. Using chick embryos as the model system
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to better understand community perspectives and identify culturally appropriate engagement approaches. Prepare the ethics application and develop participant-facing materials. Contribute to the public
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, working closely with Professor Nora Pashayan. The successful candidate will focus on developing ethnicity-specific risk thresholds that more accurately reflect the variations in breast, ovarian, and
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. Initial analysis suggests recurrent selection of divergent types in multiple locations. The aim of this role is to complete this analysis and prepare a manuscript for submission for publication
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Cambridge, Cambridgeshire, UK. The key responsibilities and duties are to perform experiments with liquid-fuelled and hydrogen flames, employ laser diagnostics, analyse the results, prepare presentations
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diversity. We work to identify the genes that regulate plant development, describe the evolutionary histories of these genes, and connect the molecular evolution of developmental genes to the evolution
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Research Council Career Development Award, or European Research Council Starting Grant. The award will be held in CITIID, either within the Jeffrey Cheah Biomedical Centre or within the University
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dispersion - and develop a system to disperse the particles. The project will explore the options for dispersion and the options for nozzle design and whether substantial additional air supply is needed
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, at the University of Cambridge, UK. The Postdoc will work together with a team of students and research collaborators on the development of learning-based discovery of robot task/environment designs