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to decipher the regulatory code controlling gene expression in plants through the engineering and large-scale validation of synthetic promoters. Within the ERC-funded multiCODE project, we aim
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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innovative strategies to improve human health. HT is composed of five Centers: Neurogenomics, Computational Biology, Structural Biology, Genomics, and Health Data Science. The Centers work together to enable
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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of substitution models using large dataset, successful applicants must then have a PhD and demonstrated experience in discrete choice models, machine learning techniques, big data, and optimization
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class of medicines. However, progress in this area has been limited by the absence of high-quality, large-scale protein¿peptide interaction datasets critical for rational, AI-driven peptide design. To
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experience in life cycle assessment (LCA) and related tools for managing large data sets to evaluate natural resources needed to advance emerging technologies. The candidate will lead their primary project and
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in the Peng Lab at UCLA The Peng Lab at the University of California, Los Angeles, is seeking highly motivated Postdoctoral Scholars with expertise in data science and bioinformatics to drive
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Texas is a leader in developing science- and data-informed tools for advancing disaster resilience and supporting public policy across the state. Through efforts such as the Texas Disaster Information
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complements LCAB’s research programmes. High competence in the analysis of large ecological and other data sets and time series. Ability to write up research for publication in high profile journals, along with