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national scientific meetings Compile data and communicate findings through research manuscripts Choose Duke. Join our award-winning team as identified by Forbes magazine as America’s Best Large Employer 2024
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team. · Applies statistical methods to large-scale, longitudinal training-related behavioral data. · Maintains substantial knowledge of state-of-the-art principles and theories
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. The postdoctoral fellow will join a research group with potential access to large, administrative data sets therefore prior experience with big data and administrative data will be advantageous. via Unsplash
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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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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 8 hours ago
. Quantifiable information about polynya dynamics can be obtained from satellite imagery revealing long, regularly-spaced 'windrows' of nascent ice crystals generated by a subsurface flow known as Langmuir
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make a difference in the world! Position Information The Postdoctoral Research Associate is responsible for assisting in the development and application of large-scale modeling frameworks for water and
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an emphasis on program planning, program evaluation, qualitative and mixed-methods data management, and community-based research. Prepares proposals and reports for funding agencies, engaging with partner
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implementation of novel training strategies under experimental constraints, e.g., active learning and other data-efficient approaches Conduct large-scale benchmarking and comparative evaluation of gene
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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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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | about 1 month ago
data analysis methods to study biological memory circuits and their applications to machine learning. Building on recent work from the Fiete Lab, the role focuses on identifying principles of biological