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Field
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of foundational and agentic AI models (LLMs, generative AI, RAG-based architectures) for autonomous, context-aware decision-making. Researching and implementing trustworthy human-machine interaction methods
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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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deploying an AI project. This includes initial problem specification, data gathering and analysis, model creation, and implementation. Applicants should be willing to learn and use agentic AI to build and
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, preferably related to serious games and/or agent-based modeling and simulation Desired experience: 2 to 5 years of professional experience Where to apply Website https://www.aplitrak.com/?adid
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, preferably related to serious games and/or agent-based modeling and simulation Desired experience: 2 to 5 years of professional experience Where to apply Website https://www.aplitrak.com/?adid
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for extension. We are looking for someone to join our team of consumer behaviour scientists and agent-based modellers who can bring knowledge of and experience with modelling cognitive or behavioural change
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engineering discipline. Experience: The ideal candidate should have some knowledge and/or experience in several of the following topics (ordered by importance): Large language models and LLM-based agents Multi
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deploying an AI project. This includes initial problem specification, data gathering and analysis, model creation, and implementation. Applicants should be willing to learn and use agentic AI to build and
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deploying an AI project. This includes initial problem specification, data gathering and analysis, model creation, and implementation. Applicants should be willing to learn and use agentic AI to build and
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farmer livelihoods. We seek candidates with expertise in landscape ecology, agroecology, ecosystem services, conservation/restoration decision-making, agent-based modelling, or related fields. The PDF will