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huge data storage capacity to accelerate the research performed in intensive computing and large-scale data analytics (Big Data). This characteristic distinguishes the HPC center at the university from
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perovskite thin films applications using slot-die coating and other large-area deposition methods. Analyze experimental data to optimize material and device performance, write scientific reports, and publish
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Associate: Physics- Informed Data Driven Windfarm Modelling For this position the research activity will apply and advance on fast CFD methods for full wind farm simulation based on Large-Eddy-Simulation
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candidate will be working with a large database comprised of prairie and marsh vegetation observations, fine-scale LiDAR data-derived ground elevations, Everglades-wide hydrological modeling and observations
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detection framework for tipping points. Contribute to the design of scalable and interpretable forecasting strategies for large climate simulators, integrating adaptive sampling and Bayesian techniques
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software delivery f) big data visualization g) cloud computing h) web application development i) NetCDF and Zarr data models f) earth system model development. Experience with software development, analysis
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Anders Ståhlberg’s research group at Sahlgrenska Center Research for Cancer. Our long-term goal is early cancer detection and to personalize the treatment of each patient. Additional information about the
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PostDoc in "Sustaining the keystone: Rethinking Antarctic krill fishery management under climate ...
ecosystems. Your Profile A PhD in marine biology, conservation biology, fishery management & conservation, or related fields A strong background in handling large data sets, programming (preferably in R
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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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at the Barts Cancer Institute (Queen Mary University of London). This role will involve analysing existing spatial-omics data sets and developing novel computational tools to understand the risk of developing