[Remote] Research Scientist - Meteorological Modeling & Analysis
Note: The job is a remote job and is open to candidates in USA. Leidos is a leading company in the defense sector, currently seeking a Research Scientist to support the Defense Threat Reduction Agency's Environmental Data Enterprise. The role involves utilizing expertise in atmospheric science and meteorology to enhance numerical weather prediction and atmospheric transport and dispersion modeling through advanced AI and machine learning techniques.
Responsibilities
- AI-Driven Model Development: Design, develop, and implement novel AI/ML methods for creating, assessing, and modifying vast amounts of meteorological data
- Advanced R&D: Conduct research on improving meteorological model inputs (e.g., planetary boundary layer, vertical mixing, ensemble forecasting) for ATD models using AI techniques to increase accuracy and efficiency
- Model Validation: Participate in research on best practices to implement and integrate verification and validation methods for NWP models for application within the ATD environment
- System & Data Integration: Explore and design new processes to assist in the intelligent selection of meteorological data based on defined Chemical, Biological, Radiological, Nuclear, and high Explosive (CBRNE) scenarios
- Data Pipeline Management: Support the ingestion, quality checking, parsing, and storage of on-demand environmental data, including ocean, surface, and upper-air observations
- Software Development: Extend, improve, and develop software that bridges the gap between research and operations, and assist in the integration of software into DoW tools
- Operational Support: Provide subject matter expertise and technical assistance on the EDE system, including monitoring system status and recommending software or hardware enhancements to streamline operations
Skills
- Master's degree and 6 years experience or a Ph.D. and 3 years experience in Atmospheric Science, Meteorology, Data Science, Computer Science, or a related physical sciences or engineering field
- Ability to obtain and maintain a DoW security clearance. Must be a U.S. Citizen
- Proven experience in developing and applying Artificial Intelligence and Machine Learning (AI/ML) models to complex scientific problems
- Strong background in numerical weather prediction (NWP), atmospheric modeling, or a related geophysical field
- Proficiency in programming languages such as Python, R, or Java, with experience using scientific computing libraries (e.g., NumPy, SciPy, Pandas) and ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
- Experience handling and processing large scientific data formats like NetCDF, HDF5, and GRIB
- Familiarity with data assimilation techniques and ensemble forecasting methods
- Strong analytical and problem-solving skills, with a demonstrated ability to conduct independent research and develop innovative solutions
- Experience with atmospheric transport and dispersion (ATD) models (e.g., HPAC, SCIPUFF)
- Familiarity with DoD cybersecurity practices and information assurance standards
- Experience working in a Linux/Unix environment
- Knowledge of space weather and its impact on terrestrial systems
- Experience with deploying and maintaining operational scientific models or software
Company Overview