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of this position is to develop the survey questionnaire for the performance measurement project funded by the National Research Council of Canada. Organizational Status This position will report directly to Dr. Qian
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wave physics and strong gravity. All topics related to formation of black hole mergers and other gravitational wave sources are of high interest, both from the computational- and the theoretical site
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genome data, high-performance computing, and environmental surveillance systems. Competitive salary and support for team building, including initial positions for 2 postdocs and 1 PhD student. A
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Dr. Kumar and other Research Scientists, the Postdoc performs routine and complex laboratory procedures throughout the training period. The Postdoc participates in laboratory meetings, keeps a lab
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postdocs. You will join a new research program on the role of universities and entrepreneurial ecosystems in building deep tech startups and scaleups. You will work towards building a landmark database on
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 23 days ago
, mathematics or any related field; correspondingly, Postdocs hold a PhD or equivalent degree in the above mentioned fields. What we offer State of the art on-site high performance/GPU compute facilities
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Science, Environmental Science, Data Science, or other related fields Strong capabilities and demonstrated experience working with large climate datasets, high performance computing, and machine learning
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environments (i.e., indoor farming, greenhouse, and high tunnel settings). Our goal is to find sustainable solutions to pest problems in controlled environments. The postdoctoral associate will perform
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The Leibniz Institute of Plant Biochemistry invites applications to fill the position of PostDoc Researcher for Metabolomic and Proteomic Analysis (m/f/d) (Salary group E13 TV-L,working hours 100
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
or high-performance computing environments. - Strong background in statistical modeling and machine learning, especially applied to spatiotemporal data. - Familiarity with urban systems, urban emissions