Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
interested in: LLM -driven systems for aligning real-world health data to standards like OMOP CDM , FHIR , and UMLS Agent-based workflows that explain, refine, and adapt semantic mappings over time Hybrid
-
particular focus on data interoperability and on the integration of AI models, multi-agent systems, and intelligent workflows deployed across the Edge–Cloud–HPC Continuum. The research activities
-
: The College is especially interested in candidates whose primary strength lies in generative AI and large language model engineering, agentic AI and multi-agent systems, AI systems evaluation and
-
intelligence (AI), including autonomy, sensing and communication, and decision support systems, among others. The R&D Engineer will work collaboratively with multi-disciplinary teams across the KRI consortium
-
University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 24 days ago
, focusing on multimodal foundation models and multi-agent systems. The position will involve conducting independent and collaborative research, developing and evaluating multimodal AI models, and
-
experimentation environments, and emerging multi‑agent systems (such as trusted‑tester or early‑access AI tools) Skills Required: Ability to: travel to remote campuses (5%) and work closely with
-
: Do you have a background in energy informatics, computer science, or energy systems, and are you are interested in edge intelligence, multi-agent AI, and interdisciplinary collaborative research
-
experiments—accelerating molecule discovery. Position Summary We are rebuilding the Design-Make-Test-Analyze (DMTA) cycle, infusing scientific automation with foundation models, multi-agent systems
-
experiments—accelerating molecule discovery. Position Summary We are rebuilding the Design-Make-Test-Analyze (DMTA) cycle, infusing scientific automation with foundation models, multi-agent systems
-
. Most of our research focuses on social dilemmas, i.e., situations where poor group outcomes arise from optimal individual choices. We use this framework to study: Multi-agent Systems and AI, Social