About this opportunity
Los Alamos National Laboratory lists this Scientist 2/3 opportunity in los alamos, New Mexico. Review the employer’s description below for duties, qualifications and application requirements.
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
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Worksite address
los alamos, NM, 87545, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.