Scientist 2/3

Los Alamos National Laboratory seeks a Scientist 2/3 to advance research and development in remote sensing and data science. The role develops and applies methods to analyze sensor data, supports sensing-system design and field experiments, and communicates findings with interdisciplinary teams.

Responsibilities

• 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

Skills

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

Benefits

• PPO or High Deductible medical insurance with the same large nationwide network
• Dental and vision insurance
• Free basic life and disability insurance
• Paid childbirth and parental leave
• Award-winning 401(k) (6% matching plus 3.5% annually)
• Learning opportunities and tuition assistance
• Flexible schedules and time off (PTO and holidays)
• Onsite gyms and wellness programs
• Extensive relocation packages (outside a 50 mile radius)

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