Internship Monte Carlo Simulation Jobs in Virginia

Are you a statistician who wants to see your Bayesian models protect national security? GA-Intelligence is seeking a Statistics PhD to develop tracking algorithms that process data from heterogeneous sensors, fuse tracks across domains, and enable time-critical intelligence decisions. You'll apply statistical inference, state-space modeling, and Monte Carlo methods to multi-target tracking challenges that combine mathematical rigor with operational constraints. Your work will span algorithm research, operational analysis, and production deployment—from deriving novel filters to validating performance on classified sensor data to partnering with engineers who implement your algorithms at scale.
 
DUTIES AND RESPONSIBILITIES: 
Algorithm Research and Development: * Guide the development of state-of-the-art tracking algorithms from existing tracking literature, ensuring technical correctness.
* Develop statistical approaches to data association in multi-target, multi-sensor environments
* Derive probabilistic models for target behavior and sensor measurement processes
* Prototype algorithms in Python, MATLAB, or R and validate performance through Monte Carlo simulation
* Apply modern statistical and computational methods to emerging tracking challenges
Operational Impact: * Collaborate with intelligence analysts to understand tracking requirements and operational constraints
* Analyze tracking performance on real-world sensor data from classified systems
* Quantify and communicate uncertainty, assumptions, and limitations to support operational decision-making
* Translate operational gaps into tractable statistical problems
* Partner with software engineers to transition algorithms from prototype to production
Research Leadership: * Publish internal research on tracking advances and algorithmic innovations
* Present findings to technical staff, program managers, and government decision-makers, as well as external conferences
* Contribute to proposal development and help shape future research directions
* Mentor junior team members and future hires
* Stay current with tracking research literature and evaluate applicability to operational problemsWe recognize and appreciate the value and contributions of individuals with diverse backgrounds and experiences and welcome all qualified individuals to apply. Job Qualifications * Typically requires a bachelor's degree, master's degree or PhD in data science, applied mathematics, statistics, computer science, or related technical/quantitative discipline from an accredited institution and progressive data science experience as follows; five or more years of experience with a bachelor's degree, three or more years of experience with a master's degree, or one or more years with a PhD. May substitute equivalent experience in lieu of education. 
* Strong preference for PhD in Statistics, Biostatistics, or closely related quantitative field
* Dissertation research in Bayesian inference, state-space modeling, sequential estimation, or time series analysis
* Strong foundations in statistical inference, probability theory, statistical modeling, and Bayesian methods
* Deep understanding of state-space models, Kalman filtering, and sequential Monte Carlo methods
* Expertise in stochastic processes and time series analysis
* Proficiency in Python, MATLAB, R, or similar scientific computing languages
* Experience implementing statistical algorithms and conducting simulation studies
* Strong analytical and problem-solving abilities
* Ability to communicate complex statistical concepts clearly to technical and non-technical audiences
* Curiosity about operational applications and mission context
* Collaborative mindset—works well with software engineers, intelligence analysts, and researchers
* Ability to obtain and maintain a DoD security clearance is required. 
Preferred Qualifications: Domain Experience: * Familiarity with tracking, navigation, or multi-target systems
* Experience with sensor fusion or data association problems
* Knowledge of Extended Kalman Filters, Unscented Kalman Filters, particle filters, or IMM filters
* Understanding of coordinate transformations and reference frames
Research Background: * Contributed to peer-reviewed publications, technical reports, or conference presentations
* Experience with probabilistic programming frameworks
* Dissertation work involving real-world sensor data or applied problems
* Prior internships or collaborations with defense, aerospace, or robotics organizations
* Experience writing technical proposals for government research projects
* Experience leading technical projects or mentoring junior researchers
Technical Breadth: * Programming experience in one or more languages such as Python, C++, Java
* High-performance computing or numerical optimization
* Version control (Git) and collaborative development practices
* Exposure to real-time systems or computational constraints
Why Join GA-Intelligence Operational Impact: Your tracking algorithms will run in production systems supporting intelligence analysts and military personnel. Your work directly contributes to national security missions. Technical Challenge: Multi-target tracking in adversarial environments with heterogeneous sensors is an unsolved research problem. You'll tackle cutting-edge algorithmic challenges that combine statistical rigor with operational constraints. Collaborative Environment: Work alongside tracking mathematicians, software engineers, intelligence analysts, and mission experts. We value diverse perspectives and believe the best solutions emerge from multidisciplinary collaboration. Our team is committed to advancing the state-of-the-art in tracking while maintaining a culture of innovation, integrity, and teamwork. Research Opportunities: Continue publishing research, present at conferences, and contribute to the tracking research community while delivering operational capabilities. Charlottesville Location: * Blue Ridge Mountains and Shenandoah National Park (30 minutes)
* University town culture with intellectual community (University of Virginia)
* Short average commute (no DC Beltway traffic)
Career Growth: * Build and lead tracking algorithm research team over time
* Technical leadership opportunities
* Shape strategic direction of tracking capabilities