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homogenisation and energy group structure. Investigate the use of AI/ML algorithms to predict or generate cross sections, enabling deterministic solvers to better capture strong heterogeneities and flux gradients
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for a Research Assistant Professor position. We seek candidates whose research examines how increasingly agentic AI (e.g., large language models, algorithmic systems) shape users’ psychological and
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algorithm that allows accurate simulation of fluid transport processes in porous media coupled with chemical reactions (e.g. dissolution and precipitation). The algorithm will be validated firstly against
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. You will contribute to developing datasets, baseline models, personalized learning engines, reasoning-graph representations, cross-domain mapping algorithms, and RLHF-style feedback loops that improve
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will examine the suitability of NIST-standardised post-quantum cryptographic (PQC) algorithms in realistic network settings and explore hybrid approaches that combine classical and post-quantum
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, nonlinear dynamical systems, robotics, and formal methods to develop principled models and algorithms for distributed decision-making in complex and uncertain environments. Your research The candidate will
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) algorithms in realistic network settings and explore hybrid approaches that combine classical and post-quantum techniques. The project will involve protocol design, system-level evaluation, and performance
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algorithms. Investigate the use of LLMs as agents or interfaces for querying building data and optimizing control parameters. Validate methodologies using real-world data from built environment monitoring and
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. Bega, M. Gramaglia, S. Geissler, C. Karsai, P. Serrano, “FARO: a scalable and reliable outage detection algorithm for IoT Mobile Virtual Network Aggregators”, ACM CoNEXT 2025 M. Milani, D. Bega, M
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to run these algorithms, i.e., the AI data centers, are extremely power hungry, thus significantly increasing the burden on the electrical grid. More importantly, the unique AI data centres load patterns