Scientist 2/3

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

What You Will Do

This position is open for external candidates only to apply.

This position will be filled at either the Scientist 2 or Scientist 3 level, depending on the skills and experience of the selected candidate. Additional responsibilities will be assigned at the higher level. The Space Remote Sensing and Data Science Group, ISR-6, at Los Alamos National Laboratory is seeking a scientist to contribute to cutting‑edge research and development in remote sensing, data science, image processing, signal processing, machine learning, and sensor data exploitation.

What You Will Do

This position is open for external candidates only to apply. This position will be filled at either the Scientist 2 or Scientist 3 level, depending on the skills and experience of the selected candidate. Additional responsibilities will be assigned at the higher level. The Space Remote Sensing and Data Science Group, ISR-6, at Los Alamos National Laboratory is seeking a scientist to contribute to cutting‑edge research and development in remote sensing, data science, image processing, signal processing, machine learning, and sensor data exploitation.

ISR-6 develops advanced methods and technologies for collecting, processing, analyzing, and interpreting data from space, airborne, ground-based, and laboratory remote‑sensing systems. We are interested in candidates with strong technical foundations in image processing, signal processing, statistical analysis, computational modeling, scientific data analysis, or applied machine learning/AI. Experience with any specific sensing phenomenology is welcome but not required.

In this role, you will contribute to one or more of the following areas:

• Developing algorithms for processing, analyzing, and interpreting image, spectral, time-series, RF, optical, or other sensor data
• Applying statistical, mathematical, machine‑learning, AI, or physics‑informed methods to detection, estimation, characterization, and inference problems
• Supporting source‑to‑sensor modeling, including source behavior, propagation, sensor response, and measurement uncertainty
• Analyzing experimental or field‑collected data and comparing results with theoretical, simulated, or modeled expectations
• Contributing to the design, characterization, calibration, and optimization of sensing systems and instruments
• Participating in laboratory, field, or deployment activities to collect and evaluate remote‑sensing data
• Communicating technical results through reports, presentations, publications, and collaboration with interdisciplinary teams
• Support field experiments at national and, as needed, international locations

What You Need

Minimum Job Requirements:

The successful candidate will have many of the following qualifications:

• Background in engineering, physics, applied mathematics, computer science, data science, or a related technical field
• Experience conducting basic or applied research, engineering development, or technical analysis relevant to sensing, imaging, signal processing, scientific computing, machine learning, or sensor data analysis
• Working knowledge of image processing, signal processing, statistical analysis, numerical methods, machine learning, or related data‑analysis techniques
• Experience using scientific programming tools or languages such as Python, MATLAB, C/C++, Julia, IDL, or similar
• Demonstrated ability and enthusiasm for leveraging modern AI/agentic systems to accelerate scientific research, software development, data analysis, or engineering workflows.
• Familiarity with one or more types of sensor or measurement systems, which may include cameras, focal plane arrays, optical systems, RF systems, acoustic/vibration sensors, spectral sensors, data‑acquisition systems, laboratory instrumentation, or field sensors
• Ability to work effectively both independently and as part of an interdisciplinary team
• Clear written and oral communication skills, including the ability to contribute to technical reports, presentations, or publications
• Ability to obtain and maintain a DOE Q clearance, which generally requires U.S. citizenship

Additional Job Requirements For Scientist 3

In addition to the Job Requirements outlined above, qualification at the R&D Engineer 3 level requires:

• Extensive experience applying image/signal processing, statistical methods, applied math, machine learning, or scientific computing to complex problems
• Proven ability to develop, implement, or improve algorithms for sensor data analysis
• Experience handling various data types, including imagery, spectral, time-series, RF, optical, vibration, or multi‑sensor data
• Familiarity with advanced areas such as Fourier analysis, estimation theory, sparse signal methods, image reconstruction, spectral analysis, sensor fusion, machine learning, anomaly detection, physics‑informed ML, scalable data processing, or sensor calibration
• Ability to link physical concepts, data traits, and computational techniques for effective analysis
• Experience leading technical tasks or mentoring, coordinating teams, or contributing to proposals

Education/Experience Scientist 2:

Positions requires a Bachelor' degree in a STEM field from an accredited college and university and 4 years of related experience, typically with post‑doctoral research experience at a university or national lab or equivalent experience directly related to the occupation.

Education/Experience Scientist 3:

Position requires a Master's degree in a STEM field from an accredited college and university and 6 years of relevant experience or an equivalent combination of education and experience directly related to the occupation.

Desired Qualifications:

Experience in the following areas are beneficial but not required:

• Remote‑sensing systems: optical, infrared, spectral, RF, acoustic, vibration, and other sensing modalities
• Machine learning, deep learning, computer vision, statistical modeling, anomaly detection, and physics‑informed AI
• Large data sets, data management, data pipelines, high-performance computing, GPU‑based computing
• Scientific computing and ML software ecosystems: NumPy, SciPy, scikit‑learn, PyTorch, TensorFlow, JAX, OpenCV, or similar
• Experimental design, laboratory measurements, field data collection, instrument characterization
• Reusable scientific software development, collaborative software environments, version control