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thinking, and analytical reasoning. High level of English. Advantageous: Experience with Python and/or MATLAB. Experience with health data, metabolomics, chemical instrumentation data, or sensor signals
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 11 days ago
orbit (LEO) sensors Integrate and test the impact of UV AOD observations from hyperspectral sensors in LEO and GEO orbits on the aerosol analysis and forecast utilizing the JCSDA-Joint Effort for Data
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intelligence (AI), and smart mobility every day. Our education and research are directly aligned with what society needs now and in the future. At TU Delft, our people make the difference. With their knowledge
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mobility every day. Our education and research are directly aligned with what society needs now and in the future. At TU Delft, our people make the difference. With their knowledge and curiosity, our staff
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for the challenges of today and tomorrow. These challenges are changing rapidly. That is why we focus on themes such as energy, climate, digitalisation, artificial intelligence (AI), and smart mobility every day. Our
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of dynamic polymer networks; (ii) (bio)material processing; (iii) organ perfusion and regeneration; (iv) tools to study mechanobiology and cell–matrix interactions; and (v) engineered drug delivery
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energy, climate, digitalisation, artificial intelligence (AI), and smart mobility every day. Our education and research are directly aligned with what society needs now and in the future. At TU Delft, our
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engineering behind the development of fusion energy, a potentially limitless energy source. PPPL is also using its expertise to advance research in the areas of microelectronics, quantum sensors and devices
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sensor measurements to embankment responses will be derived and validated using field data. These relationships will provide a framework for translating routinely collected monitoring data into actionable
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study. The research will begin with the analysis of baseline and historical data collected from wayside sensors installed on selected instrumented railway bridges. Building on these insights, an on-board