Postdoctoral Research Fellow - Agentic Modeling, Simulation & Wargaming

About Us:

VT-ARC, a technical services and applied research company, has built an organizational culture marked by four primary values: Teamwork, Integrity, Excellence, and Service. Integral to our success is our staff’s enthusiasm for solving tough problems by working together in teams to get the job done. We foster a culture where every employee’s contribution is valued and performed with integrity while maintaining a fun work environment. VT-ARC strives for excellence in all that is done for our clients, and such achievement is recognized through service/merit awards. Moreover, we promote a sense of community larger than VT-ARC alone, where staff and institutional resources can be applied in service to our country. We are proud to be the recipient of the Best Workplace in Defense Award by Emergent Magazine, an honor that recognizes companies with positive cultures that not only impact their people but also make a meaningful difference in the community.

About You:

You are a doctoral-trained researcher and systems thinker with expertise in modeling, simulation, or a related engineering discipline. You enjoy turning open-ended questions into testable models and working prototypes. You bring sound research judgment, hands-on coding ability, and curiosity about how people, technologies, decisions, and operational constraints interact. You are a self-starter who can propose an approach, write and test code, investigate unexpected results, and communicate what the evidence supports. You work independently on agreed research tasks while seeking mentorship and responding constructively to review. You want to extend your doctoral expertise into mission engineering and analytical wargaming, develop government-facing communication skills, and explore new ideas with experienced researchers and engineers.

Position Overview:

VT-ARC is seeking a Postdoctoral Research Fellow - Agentic Modeling, Simulation & Wargaming for a paid, mentored research appointment within DSD. This opportunity focuses on generative agent-based simulation, human-supervised agentic analytical workflows, and decision-support prototyping, with applications to mission engineering, logistics, mobilization, industrial capacity, and other agreed research topics.

Working with an assigned senior research mentor, the fellow will formulate research questions, design experiments, and independently code, test, and demonstrate focused proofs of concept using approved unclassified information. The appointment combines original research with development in systems engineering, mission analysis, and sponsor engagement. Prior defense employment, an existing clearance, and independent wargame leadership are not prerequisites; however, familiarity with the National Security space and/or a keen interest are critical to for the long-term success of the candidate.

The fellowship includes dedicated research exploration and values reproducible methods and well-supported negative findings. Outputs may include models, prototype software, technical papers, and presentations, subject to release approval. Production engineering, operational support, and responsibility for entire sponsor programs are outside the baseline scope; promising prototypes may transition to additional developers and specialists.

This position is a contingency hire based on a contract award expected to begin execution on or about November 01st, 2026.

Duties/Responsibilities:

• Work with an assigned senior research mentor to develop research questions, hypotheses, evaluation criteria, and a feasible work plan; propose original investigations and contribute to an individual development plan.
• Design, code, test, debug, document, and demonstrate prototype models, simulation components, data integrations, and analytical applications. Take a bounded concept through implementation and iterative evaluation.
• Develop and evaluate generative agent-based simulations and human-supervised agentic workflows, including agent behavior, task decomposition, tool use, constraints, logging, and human review.
• Design experiments and sensitivity studies; assess effects of prompts, model selection, stochastic variation, data quality, and assumptions. Compare results with baselines or reference cases and document limitations.
• Use Python and supporting development tools for data preparation, APIs, simulation execution, and analysis. Use approved AWS or comparable environments within …