Research and Development of High-resolution Satellite-based Data Products in Support of POWER p[...]

ORAU; Hampton (VA); On-site; USD 75,000 - 100,000; Full time

Job summary

A research organization seeks a scientist to innovate data accuracy and develop datasets for renewable energy applications. The role requires a Ph.D. in a related field and expertise in statistical analysis and machine learning. Responsibilities include applying advanced methods to satellite data and collaborating with end users to meet their needs. Ideal candidates will have strong programming skills and experience with NASA data products. This is an opportunity to work on impactful projects in Earth science.

Qualifications

• Ph.D. required by appointment date.
• Experience with NASA data products.
• Advanced programming skills essential.

Responsibilities

• Apply innovative methods to satellite and model datasets.
• Assess spatial and temporal variability of data products.
• Collaborate with end users for data products.

Skills

Statistical analysis expertise

Machine & deep learning method experience

Experience with time-series data

Advanced programming skills (e.g., Python, C)

Education

Ph.D. in Atmospheric Science, Earth Science, Physics, Data Science or related field

Tools

Cloud computing

Job description

Organization

National Aeronautics and Space Administration (NASA)

Reference Code

0043-NPP-NOV26-LRC-EarthSci

Description

NASA’s POWER (Prediction Of Worldwide Renewable Energy Resources) Project delivers customized data parameters from NASA’s CERES mission, GEWEX Surface Radiative Budget project, and the GMAO atmospheric reanalysis assimilation projects to support renewable energy, sustainable building, and agricultural benefit areas. This role focuses on innovating data accuracy and developing new datasets for end‑users.

The responsibilities include:

• Applying innovative methods to satellite (e.g., CERES Cloud products, TEMPO) and model datasets to create higher‑resolution products and evaluate them using surface measurements and satellite data.
• Assessing spatial and temporal variability of data products.
• Collaborating with end users to develop on‑the‑fly data products for solar, wind energy, and infrastructure decision support.
• Utilizing modern technologies such as machine/deep learning, data fusion, and cloud computing for algorithm optimization.

Field of Science

Earth Science

Advisors

Falguni Patadia – [e-mail] | [phone]

Qualifications

Ph.D. in Atmospheric Science, Earth Science, Physics, Data Science, or a related field required by the appointment date.

• Experience with time‑series data from space‑based and model observations (e.g., NASA CERES, MODIS, GPM, SMAP, MERRA, CMIP).
• Statistical analysis expertise.
• Machine & deep learning method experience.
• Advanced programming skills (e.g., Python, C, Cloud computing).
• Beneficial additional expertise: Atmospheric Radiative Transfer, High performance computing.

Eligibility Requirements

• Citizenship: LPR or U.S. Citizen.
• Degree: Doctoral Degree.

Contact

Point of Contact: Mikeala

Questions about this opportunity? Please email [e-mail].