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Qualifications • Research in mathematical applications to biological questions for multi-agent or many-body systems. • Track record in publishing in high-impact peer-reviewed journals or conferences
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GENESIS – Generative AI Agents for Software Engineering: Skills, Integration, and Satisfaction. The project is a multi-year collaboration with Ericsson and Axis Communications, aiming to investigate and
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a highly multi-disciplinary research team that includes scientists with expertise in biochemistry, bioinformatics, single cell genomics, epigenetics, pharmacology and pathology. The laboratory website
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, Computer Science and Artificial Intelligence. The position is embedded in the Multi-Agent Systems group of the department of Artificial Intelligence of the Bernoulli Institute. Qualifications PhD in Computer Science
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(or up to the end of June 2028). You will undertake original research on multi-agent reinforcement learning to coordinate grid-edge flexibility across spatial and temporal scales, while accounting
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disciplines, namely Mathematics, Computer Science and Artificial Intelligence. The position is embedded in the Multi-Agent Systems group of the department of Artificial Intelligence of the Bernoulli Institute
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University of Arizona working in the area of reinforcement learning, multi-agent systems, neuro-symbolic AI, and trustworthy intelligence. We invite qualified candidates to join our group and participate in
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Initiative’s mission, potentially including studies on political dimensions of risk frameworks, economic subsystem coupling, and multi-level agent interactions. The successful candidate will participate in
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Expert in advanced machine learning such as multi-agent generative AI, LLMs, Diffusion models, and traditional machine learning techniques Expert in CALPHAD-based ICME techniques Expert in combining
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interaction, safe exploration, long-term monitoring). You will be responsible for developing new techniques for single- or multi-agent decision-making under uncertainty in the context of autonomous systems