Research Scientist - Meteorological Modeling & Analysis

Leidos•Fort Belvoir, VA

18h•$107,900 - $195,050•Remote

About The Position

The Intel Sector at Leidos currently has an opening for a Research Scientist to work in Fort Belvoir, VA. This is an exciting opportunity to use your experience to support the Defense Threat Reduction Agency's (DTRA) Environmental Data Enterprise (EDE). In this mission, we support the environmental modeling activities of DTRA, DoW, international partners, and private industry, with a focus on atmospheric transport and dispersion (ATD) modeling. This is a full-time remote opportunity. The successful candidate will be a subject-matter expert in atmospheric science or meteorology and will take part in research and development efforts to enhance our numerical weather prediction (NWP) and ATD capabilities. The candidate will apply their expertise by using cutting-edge artificial intelligence and machine learning techniques and best software development practices to improve current capabilities and create new state of the art techniques for the evaluation and use of environmental data. This role is pivotal in designing, developing, and deploying next-generation environmental modeling systems that are crucial for national security.

Requirements

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.

Nice To Haves

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.

Responsibilities

Design, develop, and implement novel AI/ML methods for creating, assessing, and modifying vast amounts of meteorological data.
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.
Participate in research on best practices to implement and integrate verification and validation methods for NWP models for application within the ATD environment.
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.
Support the ingestion, quality checking, parsing, and storage of on-demand environmental data, including ocean, surface, and upper-air observations.
Extend, improve, and develop software that bridges the gap between research and operations, and assist in the integration of software into DoW tools.
Provide subject matter expertise and technical assistance on the EDE system, including monitoring system status and recommending software or hardware enhancements to streamline operations.