Postdoc: Vision & ML for PV Fleet Analytics

NLR; United States; On-site; USD 77,000 - 126,000; Full time

Benefits offered by this job

Medical insurance

Pension benefits

Paid holidays

Relocation assistance

Job summary

The National Laboratory of the Rockies (NLR) seeks a Postdoctoral Researcher specializing in vision machine learning to advance PV fleet analysis. You will apply computer vision and ML to satellite and aerial imagery, integrating with large PV performance datasets and metadata, driving reproducible software and analyses.

You will collaborate across PV performance, geospatial analysis, ML, and energy systems teams, contributing to publications and conference presentations while developing

Qualifications

• Recent PhD graduate within the last three years.
• Demonstrated experience with computer vision and/or machine learning, especially image segmentation, object detection, feature extraction, image registration, or change detection.
• Experience with satellite, aerial, remote-sensing, or geospatial imagery.
• Experience developing or adapting algorithms for large image datasets.
• Experience with parallel computing, HPC, distributed computing, or cloud-based workflows.
• Experience with large-scale time-series or operational datasets.
• Experience integrating heterogeneous datasets (imagery, geospatial data, operational measurements, metadata).
• Experience validating computational methods, including accuracy, uncertainty, and limitations.
• Experience with scientific ML tools (PyTorch, TensorFlow, OpenCV, scikit-learn, GDAL, Rasterio, GeoPandas, xarray) and PV-related energy data.
• Experience developing open-source scientific software or reusable computational tools.

Responsibilities

• Develop, adapt, and validate computer-vision and machine-learning methods for PV systems from satellite and aerial imagery.
• Create methods to detect and characterize changes in PV systems over time.
• Process and analyze large geospatial, image, and PV datasets.
• Integrate image-derived info with PV performance data and metadata.
• Build scalable computational workflows for large PV fleets and imagery.
• Assess algorithm accuracy, uncertainty, limitations, and generalizability.
• Develop reproducible research software and data-analysis workflows.
• Apply statistical and ML approaches to detect changes and trends in PV performance.
• Publish results in peer-reviewed journals and present at conferences.

Skills

computer vision

machine learning

geospatial analysis

data integration

HPC / parallel computing

time-series data

PyTorch

TensorFlow

OpenCV

scikit-learn

GeoPandas

xarray

GDAL

Rasterio

Education

PhD (recent, within last 3 years)

Tools

PyTorch

TensorFlow

OpenCV

scikit-learn

GDAL

Rasterio

GeoPandas

xarray

Job description

The National Laboratory of the Rockies (NLR) seeks a Postdoctoral Researcher specializing in vision machine learning to advance PV fleet analysis. You will apply computer vision and ML to satellite and aerial imagery, integrating with large PV performance datasets and metadata, driving reproducible software and analyses.

You will collaborate across PV performance, geospatial analysis, ML, and energy systems teams, contributing to publications and conference presentations while developing