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of Communication and Information (WKWSCI) to integrate geospatial modelling, behavioural risk-perception research, agent-based simulation, and community engagement design in support of Singapore’s coastal adaptation
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simulations that can aid in policy design. The Research Assistant will be work closely with the Principal Investigator and other group members on this project. Key Responsibilities Develop LLM-based agent
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architecture, and prompt deisgn to the empirical validation of the simulations. Key Responsibilities Develop LLM-based agent architecture representing diverse personas for multilingual and multicultural
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learning-based model predictive control (MPC) algorithms for multi-agent multirotor drone navigation around vessels in maritime environments. The role will focus on integrating multirotor crash predictions
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analytics, or network analysis. • Experience in agent-based modeling or simulation is highly desirable. • Demonstrated ability to publish in internationally recognized peer-reviewed journals
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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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. Familiarity with immersive platform development (e.g., Roblox, Minecraft), including scripting (Lua/Java), agent behavior modeling, event handling, and API-based integration with external AI systems. Experience
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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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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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agents (VLMs) capable of learning to operate complex, proprietary scientific software tools. This thrust emphasizes agent safety, error recovery, and tool-use. Benchmarking, Simulation & Evaluation