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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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a key role in building and integrating of AI agents into gaming scenarios (e.g., gameplay, interactions, procedural content generation, dynamic narratives), and integrating a multimodal detection
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project – “Urban smart digital services via LLM-based multi-agent collaboration”. They will be required to: (a) develop multi-agent systems; (b) conduct experimental result analysis, paper and report
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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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immunosurveillance. Macrophage-based cancer immunotherapy is considered one of the most promising fields in cancer immunology and the next generation of cancer immunotherapy. Recent publications in the Feng lab
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papers based on research findings. Developing research proposals related to multi-agent systems and their applications. Job Requirements: PhD degree in Computer Science, Artificial Intelligence, or related
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-grade codebases, including data pipelines and analysis workflows. Developing and deploying AI agents and large language model–based tools for tasks such as document processing, information extraction
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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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content moderation framework for immersive 3D virtual environments, such as Roblox and Minecraft. The research staff will play a key role in building and integrating of AI agents into gaming scenarios (e.g
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posts) [Appointment period: each for three to six months] Duties The appointees will assist the project leader in the research project – “Urban smart digital services via LLM-based multi-agent