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(Lua/Java), agent behavior modeling, event handling, and API-based integration with external AI systems. Experience with distributed systems, reinforcement learning, or simulation environments (e.g
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of the effects of insect or disease disturbances on forests across the U.S. based on forest inventory data and use a forest simulation model to project the future effects of those agents on forests
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• Support the integration of causal models within agent-based and simulation frameworks • Prepare peer-reviewed journal articles, technical reports, and policy briefs • Assist in stakeholder
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datasets • Support the integration of causal models within agent-based and simulation frameworks • Prepare peer-reviewed journal articles, technical reports, and policy briefs
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application consists of: An application Transcript(s) – For this opportunity, an unofficial transcript or copy of the student academic records printed by the applicant or by academic advisors from internal
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multi-agent frameworks. Familiarity with immersive platform development (e.g., Roblox, Minecraft), including scripting (Lua/Java), agent behavior modeling, event handling, and API-based integration with
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expertise in agent-based modelling. The models we build will have an interface with community stakeholders and mobility service providers, so we are particularly seeking applicants who are comfortable in
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programming will be advantageous. Knowledge of intelligent decision agents based on graph neural network or similar will an advantage. Key Competencies Good knowledge in reliability analysis. Experience in
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(Lua/Java), agent behavior modeling, event handling, and API-based integration with external AI systems. Experience with distributed systems, reinforcement learning, or simulation environments (e.g
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conditions and policy outcomes. Desired areas of expertise include: dynamic and complex systems, agent-based modeling, computer programming (familiarity with R, Python, Netlogo), statistical analysis