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Field
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. The research targets a new generation of intelligent agents that learn through sequential interaction, and is organized around two pillars united by a shared reinforcement learning foundation. Embodied
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data to map host-pathogen interactions and drug mechanisms of action. Developing a comprehensive, systems-level understanding of the viral life cycle, host-virus dynamics, and the pharmacological
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way patients are selected in the clinic to receive oncological treatments. This will also advance our understanding of the mechanisms of interaction between multiple types of tissue and cells given a
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for cotton jassid, emphasizing microbial control agents, including entomopathogenic fungi and entomopathogenic nematodes, and evaluating their compatibility with generalist predators. Responsibilities
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application: Experience with agent-based modelling, network modelling, dynamic systems, spatial interaction models, activity-based travel modelling, transport simulation, or digital twins. Experience with
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relevant sample matrices. What you need to know Please Note: Ability to work in a biosafety level 2 (BSL-2) environment with potential exposure to bacterial agents and biohazards. This position is grant
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primary mentor on projects at the intersection of educational data science, AI in education, human-AI interaction, and the learning sciences, with additional advisory support from faculty and researchers
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Would you be interested in exploring how multi-agent aerial manipulation can contribute to construction, in particular by assembling a pavilion? Job description Advancement of aerial robotics
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-VLMs, tiny-VLAs; Agentic-AI systems; and Robust Generative AI targeting hallucination, safety and security issues. Besides robustness, systems should also be optimized for high performance and energy
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sociabilités et coopérations patrimoniales aux frontières des institutions Étudier les interactions entre : - professionnels des institutions patrimoniales - collectifs, associations, amateurs et publics