10 big-data-and-machine-learning-phd Postdoctoral research jobs at National Aeronautics and Space Administration (NASA)

A Next-Generation Wildfire Risk Assessment System: Integrating Satellite Data with Deep Learning Insights

National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 9 hours ago

observations and model-based data. Apply machine learning techniques to optimize factor weightings and reveal critical wildfire drivers. Validate models using multi-source wildfire data (MODIS, VIIRS, and NOAA

Data Science for Satellite Remote Sensing and Earth Science Research

National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | 10 days ago

. Description: The post-doctoral fellow will apply machine learning and/or other data science techniques to conduct scientific research, improve remote sensing data products and analysis, integrate machine

Geologic sources of carbonaceous gasses and their impacts on terrestrial ecology

National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 3 hours ago

quantification of geologic CO2 and CH4 emissions on large scales are challenged by the remoteness of emission sites, inaccurate attribution of emission sources, emission variability, and insufficient monitoring

Investigating Air Quality Challenges and Impacts in California’s Central Valley

National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 9 hours ago

status Questions about this opportunity? Please email npp@orau.org Qualifications PhD in atmospheric science, environmental engineering, public health, data science, or relevant disciplines. Experience

High Fidelity Modeling of Heating during Entry to the Outer Planets

National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 9 hours ago

parameters such as rate and transport coefficients, state-to-state transition data and radiation transition moments. This post-doctoral position will examine higher fidelity approaches that address thermal and

Remote Sensing from Space: NASA Biodiversity and Ecological Conservation Opportunity with the NASA Earth eXchange (NEX)

National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 9 hours ago

biodiversity trends, particularly in response to Earth system variability, land-use change, and other shifting environmental conditions and stressors. Integrating in situ data with remotely sensed observations

Computational design for spacecraft applications

National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 3 hours ago

PhD in a relevant field such as structural mechanics, heat transfer, numerical optimization, topology optimization, or lattice design. The postdoctoral scholar will be responsible for vigorously

New developments in polarimetric ground-based instrumentation for remote sensing and validation of aerosols and clouds

National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 9 hours ago

. Description: NASA has been making regular global measurements of aerosols and clouds from space for more than two decades. Validation of the accuracy of these measurements relies heavily on data from ground

Advancing Impact Monitoring in the Era of LSST, NEO Surveyor, and ADES

National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 3 hours ago

Data Exchange Standard (ADES); (2) modernizing short-term impact monitoring through adaptive search algorithms for systematic ranging (Scout); and (3) refining long-term impact prediction via improved

NASA Foundation Models for Earth Science (Ecosystems, Biodiversity, Environmental Variable Downscaling)

National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 3 hours ago

, modeling and data assimilation, and developing digital twin technologies. Candidates can expect to work with collaborative and dynamic environment that includes fundamental and applied research performed