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Dr Helen Mulvana and an interdisciplinary team of experts based at the Universities of Nottingham and Cambridge. The successful candidate will contribute to the development of techniques for ultrasound
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focus on agent-based modeling and the quantitative analysis of spatial structures in experimental data. In doing so, you will develop your own research focus, support conceptual work, and contribute
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description] Research on the development of cognitive models for nonverbal communication channels between AI agents, as well as duties related to the research project. * Assigned department Existing departments
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intelligent research training systems. The successful candidate will join a multidisciplinary team conducting applied research in simulation-based training, modeling, and opportunity-based training systems. Key
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. • Share concerns appropriately by avoiding direct confrontation in staff meetings: supporting in public, confronting in private. • Participate in RA selection and evaluation processes. • Role model
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certification based on proof of validity and reproducibility. The R&D questions concern : (For P1) "AI as a service" to enrich engineering: modelling of the changing, complex and uncertain environment
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to set your own research priorities within the project Desirable skills, but not essential: Initial experience with agent-based modeling, Programming skills Our Offer: We work on highly topical, socially
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at the interface of Fintech and AI, and in areas related to computational finance and financial engineering, for example: AI for finance, automated trading, agent-based modelling of financial systems, blockchain
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for the fast adaptation of large vision-language agentic models, including supervised and reinforcement learning. The project team at HSP is responsible for all the phases of the research development and within
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develop novel robotics research projects in the field of metric-semantic mapping, semantics-driven active exploration, and foundation models-aided intelligent decision systems, with an additional objective