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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 20 hours ago
. Description: Characterization of the near Earth space environment, extending to Lunar, cis-lunar and near-Mars environments, is critical for the health and operation of both crewed and robotic missions as
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APPLICATION INSTRUCTIONS: CURRENT PENN STATE EMPLOYEE (faculty, staff, technical service, or student), please login to Workday to complete the internal application process . Please do not apply
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electronic conversion, energy and hydrogen storage, downstream processes, and energy demand—to enable more efficient, flexible, and economically viable Power-to-X operation. This position is expected to start
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postdoctoral position lies at the interface of fluid mechanics, phase-change physics, and industrial application. It is part of ARCNL’s Source Department and the EUV Plasma Processes group. We investigate
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, and linked to individual identity. The TREM project aims to better understand the processes underlying the transition from traumatic autobiographical memory to resilient memory, placing central emphasis
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will support and conduct simulation modeling research related to tobacco and lung cancer prevention and control. Duties include: Conducts data analysis using secondary data sources, such as national
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. Experience and expertise in human mobility simulation and prediction with agent-based modeling and deep learning techniques. Proficient in Python programming for geospatial data processing, modeling, and
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Classification Title: Postdoctoral Associate - Keeler Lab Classification Minimum Requirements: • PhD degree (within 2 years) or be in the process of completing a PhD in biological sciences (e.g
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about the range of information about you processed by the controller; − access to your data and receiving a copy of the data (this does not apply to copies of the documents themselves); − rectification
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05.07.2026, Academic staff Our research combines mathematical modeling, numerical simulation, scientific computing, and data-driven methodologies to improve the predictive capabilities and