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This post of Research Assistant (pre-doctoral) or Research Associate (post-doctoral) is to conduct research on cloud computing and future cloud infrastructure, under the direction of Dr. Marios
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planetary health— located in Ithaca, NY, invites applications for a Postdoctoral Research Associate in Transportation Systems Modeling, Computing, and Cloud-Based Mobility Analytics Platforms as part of
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backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and ICT Services
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health record (EHR) integration Community partnership–driven research Responsibilities: Conduct statistical and computational analyses using R, Python, SAS, and/or SQL Support cloud-based analytics in
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Environmental science » Earth science Mathematics » Applied mathematics Physics » Acoustics Physics » Chemical physics Physics » Computational physics Physics » Other Researcher Profile Recognised Researcher (R2
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websites https://www.augusthuanglab.org/ and https://www.khoshkhoolab.com/ . Candidate qualifications include: PhD and/or MD in computational biology, bioinformatics, genomics, or other related fields
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environment. Other Required Skills and Abilities Demonstrated ability to manage and analyze large, multi-modal datasets. Familiarity with cloud computing environments (e.g., Google Cloud) and version control
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Research Framework Programme? Other EU programme Reference Number 11/2026 Is the Job related to staff position within a Research Infrastructure? No Offer Description Applications invited for the following
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vision and novel applications of machine learning. Advanced knowledge of R or Python is required. Intermediate knowledge in C/C++ and/or at least one SQL dialect is preferred. Apply online at https
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National Aeronautics and Space Administration (NASA) | New York City, New York | United States | 4 days ago
representation and speed of computation for GISS climate model, particularly the treatment of cloud inhomogeneity in GCM grid scale (~200 Km) and the improvement of K-distribution parameterization for gaseous