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Field
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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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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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to marine terminating glacier stability, changes in iceberg calving behaviour, and the trajectories and lifespans of icebergs. This will involve working with satellite data currently held in the cloud
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 9 hours ago
surface, aerosols, clouds, and climate change. In-house capabilities include design and development of novel airborne instruments for aerosol, cloud and trace gases systems. For the past year, we hosted a
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dependable large-scale software systems, integrating expertise in: Software Engineering Machine Learning & MLOps Robotics & Cyber-Physical Systems Cloud & HPC ecosystems Interdisciplinary research. As a
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 1 month ago
deployment (e.g., Docker) and cloud/serverless architectures (AWS SAM, Lambda, Amplify); experience with React or web and mobile application development; familiarity with GitHub; excellent project management
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. The candidate will need to master sensor technologies, embedded systems, and communication protocols, while integrating real-time data into cloud platforms to develop reliable, secure, and scalable solutions
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 3 hours ago
: Jovian clouds, Callisto craters, Europa chaos blocks, Triton plumes, or other topics. Field of Science: Planetary Science Advisors: Conor Nixon conor.a.nixon@nasa.gov (301) 286-1234 Applications with
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with high-performance computing (HPC) environment, cloud-based computation, software tools for genetic epidemiologic analyses (e.g. GWAS, whole-genome sequencing, polygenic score, Mendelian Randomization
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biological data. · Proficiency in R and/or Python for data analysis and visualization. · Experience working with large datasets in an HPC or cloud computing environment. · Demonstrated ability to work