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the next generation of secure agentic AI systems through cutting-edge research in adversarial machine learning and formal verification. The Role As a research scientist, you will contribute to frontier AI
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agents (OHRP, FDA, DOD, etc.) as needed for guidance to ensure UMCIRBs satisfaction of regulatory requirements. Draft and maintain Individual Investigator Agreements with individual research team members
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adaptation of existing approaches for scientific applications; (ii) Large Language Models (LLMs) and multi-modal foundation Models (iii) Agentic AI techniques for scientific domains; and (iv) techniques
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identification elements)*; Experience in developing multi-agents with LLM. * mandatory requirement Work plan: The candidate will carry out R&D activities within the scope of the operation A-MoVeR - Agenda
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three years ago; - Relevant experience in conducting research in IoT, Multi-agent Systems, Asset Administration Shells, and RAMI4.0; - The candidate's training and experience must be appropriate
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organization for research publications, with potential for co-authorship. Additional details of these responsibilities are provided below: Coordinate the conduct of complex (i.e., multi-drug regimens, high
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and artificial intelligence. This role offers a unique opportunity to support the development and evaluation of a multi-agent Retrieval-Augmented Generation system designed to accelerate understanding
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relation with energy generation, CO2 sink building materials synthesis and materials recycling. In the frame of this project, the recruited researcher will specifically work on: (i) the multi-scale
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workflow optimization • Network, graph, and agent-based modeling for care delivery • Health equity, patient access, and system resilience • Multi-modal data integration using EHR, claims, environmental, and
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four (4) years of post-degree experience in computational systems modeling, simulation, and analytics. Experience with agent-based, biophysical modeling, or multi-scale modeling; OR Experience with