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improve malaria surveillance and control. Given the multidisciplinary nature of the project we welcome applications from candidates who hold a PhD in a range of fields including computer
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. DESIRABLE EXPERIENCE Ecosystem monitoring and vegetation indices. Time-series analysis of environmental or satellite data. Cloud-based geospatial computing and large-scale data synthesis. CONTRACT DETAILS
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academic 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
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Positions Application Deadline 18 May 2026 - 23:59 (Europe/Paris) Country France Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a
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academic 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
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or an equivalent foreign degree in Mechanical Eng., Naval/Maritime Eng., Meteorology, Atmospheric Physics, Chemical Eng., Physics, Mathematics, Aeronautics or any relevant PhD program. This eligibility
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The Nicolaus Copernicus Astronomical Center of the Polish Academy
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bring strong research expertise and strong technical skills within remote sensing and ecology, notably lidar processing. The successful candidate should have: Required: A PhD degree with a publication
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engines and natural cirrus clouds, hours to days after the emission. You will have, or be close to completing, a PhD in climate science, meteorology or related fields. Ideally, you will also have strong
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National Aeronautics and Space Administration (NASA) | New York City, New York | United States | about 2 months 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