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of multi-agent systems Control and containment: Developing steering techniques and safety measures to guide model behavior, including red-teaming and methods for intervention, guardrails, and safety
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intelligence that coordinates the entire experimental ecosystem. The Postdoctoral Fellow will develop agentic AI models and frameworks for intelligent experimental workflows, which couple machine learning, real
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based chatbot to instill lifestyle changes including making meal recommendations with appropriate guardrails in place. Key Responsibilities: Developing LLM agentic framework for detection of food, making
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of multi-agent systems Control and containment: Developing steering techniques and safety measures to guide model behavior, including red-teaming and methods for intervention, guardrails, and safety
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. • Familiarity with agent-based and compartmental models for infectious diseases. The grade of appointment will be accorded based on candidate’s academic qualifications and years of relevant experience. Applicants
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within the team under the Principal Investigator Assistant Professor Borame Dickens alongside multiple collaborators and experts. Methods include agent based/individual based modelling, SEIR modelling
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Postdoctoral Research Fellow in Multimodal Foundation Models and Biomedical AI – AI/CS-Oriented Role
interdisciplinary team at the intersection of artificial intelligence, health, and neuroscience. This position focuses on developing next-generation multimodal foundation models and agentic AI systems that can reason
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Postdoctoral Research Fellow in Multimodal Foundation Models and Biomedical AI – AI/CS-Oriented Role
interdisciplinary team at the intersection of artificial intelligence, health, and neuroscience. This position focuses on developing next-generation multimodal foundation models and agentic AI systems that can reason
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scientific understanding and drive innovation through agent-based models, population models, and software implementations. This unique opportunity allows you to shape the future of biological research while
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institutions, including Politecnico di Torino, to advance scientific understanding and drive innovation through agent-based models, population models, and software implementations. This unique opportunity allows