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disease trajectories. The project is part of a Nordic initiative in large scale healthcare data analysis for development of precision medicine approaches. The researcher hired for this postdoctoral fellow
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interdisciplinary study that will assess the pre-/and post-radon concentrations following deep energy-retrofits scenarios of the large-scale national renovation strategy. INFORM will utilise a building physics model
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. The post-holder will participate in lab meetings, journal clubs, departmental research meetings, and co-supervise students. They will also present data at high-profile international and national meetings
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Postdoc "Interferometric SAR Data Processing and Analysis for Implementation in the 3D-ABC Founda...
products from the TanDEM-X radar mission, large airborne and field-based LiDAR datasets, and process-based models, as well as other openly available remote sensing and field datasets. The diverse data will
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concentrations following deep energy-retrofits scenarios of the large-scale national renovation strategy. INFORM will utilise a building physics model (CONTAM), which will be parameterised based on representative
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or related disciplines. They should have i) a strong quantitative background; ii) experience in analysing epidemiological data using R, STATA, SAS or other statistical packages; iii) demonstrated expertise in
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
, or a related field completed before the start date of the position Demonstrated experience with astronomical data analysis and software development Proficiency in Python programming Experience with large
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tools to differences in genotypes and environment to predict disease trajectories. The project is part of a Nordic initiative in large scale healthcare data analysis for development of precision medicine
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The Section for Software Engineering and Computing Systems, at the Department of Electrical and Computer Engineering (ECE), invites applicants for a two-year postdoctoral position within the area of
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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