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bridge the fields of Generative AI, Recommendation System, Labor Economics/Organizational Science, and Social Simulation Platform. The key focus areas of this project include: 1. Agentic Career
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and Immigration website . Full-Time, Fixed-Term (until 31 August 2028) The Department of Computer Science is seeking a Postdoctoral Research Fellow for the Leverhulme-funded project “Social Mechanisms
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 2 hours ago
mission development as well as societal applications. The overarching goal of this project is to enhance ISSM’s capability, scalability, and accessibility by developing a multi-modular, agentic AI framework
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We are seeking a highly motivated and creative Postdoctoral Researcher to join the X-ray Science Division (XSD) at Argonne National Laboratory. The successful candidate will develop web-based AI
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and fine-tune LLM Agents for hypothesis generation and protocol suggestions. Design and manage a structured, FAIR-compliant knowledge base for materials discovery. Contribute to the development and
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pipeline for predicting human pathogenicity based on bacterial genomes, something that has recently been expanded using more novel AI-techniques. There is, however, a need to further expand this to also
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and integrate emerging AI techniques (e.g., agentic workflows, LLMs) into scientific problems, ensuring methods effectively solve real domain challenges. Advanced Model Development: Design and debug
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of an Interdisciplinary System Foundation for a Symbiotic and Collaborative Society with Humans and AI.” This position is part of the project “Establishing Nonverbal Communication Channels to Promote Human–AI Coexistence
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Postdoctoral Appointee - Investigation of Electrocatalytic Interfaces with Advanced X-ray Microscopy
part of the DOE–BES initiative Integrated Scientific Agentic AI for Catalysis (ISAAC) , a multi-facility collaboration integrating experimental modalities and simulations to enable an orchestrating
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workflows, and immersive or experimental interfaces Integrate LLM-based and agentic AI systems with scientific visualization frameworks, in situ pipelines, and data analysis workflows Prototype and evaluate