Remote Sensing Data Scientist II

Los Alamos National Laboratory; Los Alamos (NM); On-site; USD 90,000 - 130,000; Full time

Job summary

Los Alamos National Laboratory seeks a Scientist 2/3 level to advance remote sensing, data science, and image processing research. The role covers machine learning, signal analysis, and sensor data exploitation, with responsibilities across algorithm development, data interpretation, and interdisciplinary collaboration.

Ideal candidates have strong foundations in engineering, physics, or math, hands-on software experience (Python/MATLAB/C/C++/Julia/IDL), and the ability to work independently or

Qualifications

• Bachelor's degree in a STEM field and 4+ years of related research or technical experience.
• Experience in image/signal processing, data analysis, or scientific computing.
• Proficiency in programming languages such as Python, MATLAB, C/C++, Julia, IDL, or similar.
• Ability to apply AI/ML methods to sensing, imaging, and data workflows.

Responsibilities

• Develop and apply algorithms for processing and interpreting image, spectral, time-series, RF, or sensor data.
• Apply statistical, mathematical, and machine learning methods to detection and inference problems.
• Support source-to-sensor modeling and assess measurement uncertainty.
• Analyze experimental or field data and compare with models or simulations.
• Contribute to design, calibration, and optimization of sensing systems.
• Collaborate with interdisciplinary teams and communicate technical results.

Skills

Image processing

Signal processing

Machine learning

Data science

Python

MATLAB

C/C++

Julia

IDL

Statistics

Education

Bachelor's degree in STEM fields

Master's degree in STEM fields

Tools

NumPy

SciPy

scikit-learn

PyTorch

TensorFlow

OpenCV

Job description

Los Alamos National Laboratory seeks a Scientist 2/3 level to advance remote sensing, data science, and image processing research. The role covers machine learning, signal analysis, and sensor data exploitation, with responsibilities across algorithm development, data interpretation, and interdisciplinary collaboration.

Ideal candidates have strong foundations in engineering, physics, or math, hands-on software experience (Python/MATLAB/C/C++/Julia/IDL), and the ability to work independently or