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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 Challenge: Managing flood risk in vulnerable interconnected
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 28 days ago
Organization National Aeronautics and Space Administration (NASA) Reference Code 0326-NPP-NOV25-GSFC-EarthSci How to Apply All applications must be submitted in Zintellect Please visit the NASA
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their interactions with climate and human activities, with an emphasis on the sustainable management of natural resources (soil, land, water, and agriculture) in the context of climate change. One
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Challenge: Managing flood risk in vulnerable interconnected regions. Change: Advancing hydraulic modelling and NBS for resilience. Impact: Protecting communities with smarter adaptive strategies
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of this research is assessing the fitness of geospatial indicators to inform conceptual and policy-relevant understanding of vulnerability processes for disaster risk reduction and climate adaptation. The researcher
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-relevant understanding of vulnerability processes for disaster risk reduction and climate adaptation. The researcher will report to Professor Eric Tate at Princeton University and may collaborate with Dr
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, and their interdependencies. Develop processes for transportation route and mode identification and facility sighting, considering natural disaster resiliency, climate change, and energy affordability
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invisible thread that runs from the mundane details of life, like opening a door or using a toaster, all the way through society's biggest challenges, like health care, scaling manufacturing and disaster
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remotely sensed data. The center’s research aims to improve the understanding of surface processes and their interactions with climate and human activities, with an emphasis on the sustainable management
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. Familiarity with wildfire modeling, risk assessment, or disaster management. Strong programming skills in Python, Matlab, R, or other relevant languages. Experience working with large datasets and high