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Los Alamos National Laboratory

Just Landed

Postdoctoral Researcher in Vision Machine Learning for Photovoltaic Systems National Laboratory of the Rockies in United States

Degree Level

Postdoc

Field of study

Computer Science

Funding

Full-time postdoctoral employment at 40 hours per week with an annual salary range of $76,600–$126,400. Benefits include medical, dental, and vision insurance; short-term disability insurance; pension benefits; a 403(b) employee savings plan with employer match; life and AD&D insurance; paid time off, sick leave, and holidays. Some positions may be eligible for relocation reimbursement. Performance-, merit-, and achievement-based monetary awards may be available but are not guaranteed.

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Country

United States

University

Los Alamos National Laboratory

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Keywords

Computer Science
Environmental Science
Electrical Engineering
Remote Sensing
Geography
Energy Engineering
Computational Science
Spatial Analysis
Computer Vision
Change Detection
Photovoltaic
Statistics
ML

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About this position

The National Laboratory of the Rockies (NLR) is hiring a Postdoctoral Researcher in Vision Machine Learning for its Golden, Colorado location. The researcher will work at the intersection of computer vision, machine learning, large-scale data analytics, remote sensing, geospatial analysis, and photovoltaic (PV) system performance.

The project focuses on understanding how the U.S. photovoltaic fleet changes over time. Responsibilities include developing and validating computer-vision and machine-learning methods for satellite and aerial imagery; detecting and characterizing changes in utility-scale PV systems; processing large geospatial, image, operational, and time-series datasets; and integrating image-derived information with PV performance, permitting, metadata, and related energy-system data.

The postdoctoral researcher will contribute to scalable computational workflows, reproducible scientific software, uncertainty and accuracy assessment, and peer-reviewed publications and conference presentations. Related research may address PV fleet evolution, repowering and decommissioning, end-of-service analysis, material-flow modeling, and PV circularity.

Applicants must have completed, or be scheduled to complete, a PhD within three years of graduation and before the employment start date. Relevant experience includes computer vision or machine learning, remote-sensing imagery, large-scale computing, heterogeneous dataset integration, quantitative algorithm validation, scientific programming tools such as PyTorch, TensorFlow, OpenCV, scikit-learn, GDAL, Rasterio, GeoPandas, or xarray, and photovoltaic or renewable-energy applications.

This is a full-time, fixed-term postdoctoral position with a stated annual salary range of $76,600–$126,400, plus eligible benefits. The anticipated application closing window is up to 30 days and may be extended. Candidates should submit an application, cover letter, and resume through the NLR Workday portal.

Funding details

Full-time postdoctoral employment at 40 hours per week with an annual salary range of $76,600–$126,400. Benefits include medical, dental, and vision insurance; short-term disability insurance; pension benefits; a 403(b) employee savings plan with employer match; life and AD&D insurance; paid time off, sick leave, and holidays. Some positions may be eligible for relocation reimbursement. Performance-, merit-, and achievement-based monetary awards may be available but are not guaranteed.

What's required

Applicants must be recent PhD graduates, having completed the PhD within the last three years, and must meet the educational requirements before employment begins. Required experience includes computer vision and/or machine learning; satellite, aerial, remote-sensing, or geospatial imagery; large image datasets; parallel, high-performance, distributed, or cloud computing; large-scale time-series or operational datasets; heterogeneous data integration; quantitative validation of computational methods; relevant tools such as PyTorch, TensorFlow, OpenCV, scikit-learn, GDAL, Rasterio, GeoPandas, or xarray; photovoltaic or renewable-energy applications; and open-source scientific software, reusable computational tools, or public research datasets. Candidates must be able to obtain and maintain a federal PIV card, satisfy DOE access requirements, obtain work authorization, comply with applicable foreign government talent recruitment restrictions, and pass a pre-employment drug test.

How to apply

Apply through the Workday application portal. Submit an application form for this position along with a cover letter and resume; applications are not retained for future positions.

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