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, and agent-based modeling for care delivery Health equity, patient access, and system resilience Multi-modal data integration using EHR, claims, environmental, and behavioral datasets The successful
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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
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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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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 Systems, and Models in Biology and
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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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-degree experience in computational systems modeling, simulation, and analytics. Experience with agent-based, biophysical modeling, or multi-scale modeling; OR Experience with analyzing multi-omics data
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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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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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distributed training, experiment tracking, and MLOps automation. Problem-Solving Skills (15%) – Innovate adaptive fine-tuning, multi-task learning, and agentic reasoning strategies to improve generalization and
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 8 days ago
Lille – Nord Europe, Villeneuve d’Ascq, in the Inria team-project Scool (Sequential, Continual and Online Learning), with strong regular interactions with CIRAD AIDA unit in Montpellier. Keywords: Multi