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and chemical/biological agent detectors in the aviation, ports and borders sectors). More information about Smiths Detection can be found at: https://www.smithsdetection.com/ . The Training Alongside
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, or trustworthy AI agentic AI, multiagent systems, sequential decision making, and LLM-based reasoning embodied or physical AI, robotics, autonomous systems, or intelligent infrastructure systems strong programming
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interactions can be generated based on emerging and pre-defined protocols for interaction between agents, between agents and their environment and between agents and humans. By an interaction protocol, we mean a
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compositions of these materials with potential adsorption properties for simulants of toxic agents or catalytic properties of interest for degradation action, a molecular modeling approach based on density
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, and automation. Proficiency in modern data modeling, normalization, ELT patterns, and relational database design. Experience with Git-based version control and CI/CD workflows (GitLab CI or equivalent
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Evolution. Please check our publications for more details: http://garciajulian.com [1] “Empirical Agent Based Models of Cooperation in Public Goods Games | Proceedings of the Fourteenth ACM Conference
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LLM Agents: Foundations, Attacks, and Defenses”. Your work assignments Large language model (LLM) agents represent the next generation of artificial intelligence (AI) sys- tems, integrating LLMs with
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for cooperative autonomous driving; Design large vision-language models for autonomous driving; Design generative diffusion & 3D/4D scene synthesis models to enable multiple agents to jointly reconstruct a scene
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also connected to the Wallenberg Initiative Materials Science for Sustainability (WISE, https://wise-materials.org ). WISE, funded by the Knut and Alice Wallenberg Foundation, is the largest-ever
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, and Azure—and designs future-state structures that support data products, analytics, automation, and AI/ML enablement. Establishes enterprise data standards, models, governance structures, and