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portfolio and the wider Responsible AI landscape into clear, evidence-based policy advice for government, industry and the public. The research will focus on: Agentic AI systems and their governance Physical
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portfolio and the wider Responsible AI landscape into clear, evidence-based policy advice for government, industry and the public. The research will focus on: Agentic AI systems and their governance Physical
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environments. The security and robustness of LLM-based and agentic systems, including adversarial manipulation, uncertainty, provenance, and the validation of AI-generated decisions and actions, may also be
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on persona-based social simulations for aiding policy design. Position Overview This research project will focus on building and evaluating novel LLM-based systems for performing computational social
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innovation in persona-based social simulations for aiding policy design. Position Overview The research project will focus on building and evaluating novel LLM-based systems for performing social simulations
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of Isabelle infrastructure for AI-assisted theorem proving, including proof-data extraction, interaction with proof states, and integration of AI agents into Isabelle-based verification workflows. Work closely
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analytics, or network analysis. • Experience in agent-based modeling or simulation is highly desirable. • Demonstrated ability to publish in internationally recognized peer-reviewed journals
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discipline. Demonstrate a strong research track record in areas aligned with fluid dynamics or cell motility. Bring experience in continuum or agent-based modelling and in developing computational simulations
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, and scholarly activities. In partnership with Northeastern University, Ironwood Pharmaceuticals is offering a two-year Medical Scientific Affairs fellowship, based in Boston, Massachusetts. About
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science, Computational Social Science, Complex Systems, Operations Research, or a related field. Strong agent-based modelling expertise in Python (Mesa) and/or NetLogo. Experience with empirical ABM calibration. A track