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of applying them to data. Collaborative endeavours with members of the IPMU and Oxford groups is highly encouraged. You will have the opportunity to teach. Applicants should have a PhD (or close to completion
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of atomic environments Detection of extrapolation and low-reference data regimes Active learning in configurational and chemical space Training and benchmarking of large-scale foundational MLFF models More
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., active learning and other data-efficient approaches Conduct large-scale benchmarking and comparative evaluation of gene perturbation models across diverse single-cell datasets Collaborate closely with
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developing next-generation AI methods for healthy climate adaptation. The position will focus on building and evaluating foundation models for large-scale spatiotemporal health and environmental data. Our team
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diagnostic pathways. Core research tasks include planning, conducting and publishing epidemiological studies using large-scale observational data, primarily register-based, with a focus on effects of ADHD
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disease, including AI-powered tools and new statistical techniques that leverage large datasets, heavy computational capabilities, and/or a robust understanding of biological systems to provide unique
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activities such as working with large, longitudinal datasets, designing and implementing lab-based experiments, coding video data, writing manuscripts, presenting research, and mentoring undergraduate and
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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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and Welfare (EUPHAW) and focuses on the development of methods to quantify and analyze behavior and welfare in dairy cattle using large-scale video and sensor data collected in barn environments
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Requisition Details GENERAL REQUISITION INFORMATION EEO Statement: Location Omaha, NE Requisition Number: 2026 - 052 Department Genetics Cell Biology & Anatomy 50000507 Business Unit(College