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Operations Research and Operations Management, such as network theory, combinatorial optimization, and econometrics. The project pursues three interrelated aims: first, to characterize how network structure
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in underground facilities. The project aims to evaluate sensor technologies, design and optimize multi-sensor monitoring networks, and develop advanced detection and localization algorithms adapted
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harness advanced techniques such as machine learning, optimization algorithms, and sensitivity analysis to automate and enhance the mode selection process. The result will be a scalable methodology that
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Mobile Edge Computing (MEC) has emerged as a promising computing paradigm to support emerging high-performance applications by deploying resources at the network edge. However, most existing MEC
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: Advancing Explainability for Time Series AI Forecasting in Mobile Networks, IEEE INFOCOM 2024 [7] S. Alcala-Marin, A. Bazco-Nogueras, A. Banchs, M. Fiore, kaNSaaS: Combining Deep Learning and Optimization
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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Night pollinators – an overlooked component of pollination networks The Faculty
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optimally for future challenges. This PhD position is part of the SecReSy4You MSCA Doctoral Network, which focuses on developing next-generation methods for security and resilience of cyber-physical systems
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 24 days ago
Bubeck, Yin Tat Lee, and Laurent Massoulié. Optimal convergence rates for convex distributed optimization in networks. Journal of Machine Learning Research, 20:1–31, 2019 [5] Ohad Shamir, Nati Srebro, and
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topic: “Topology optimization and residual stress modeling for additive manufacturing of Ni₃Al-intermetallic based alloys” Supervisors: Sup. Researcher Tatevik Minasyan, Department of Mechanical and
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scales, and require high-dimensional parameterizations. A single high-fidelity simulation of the full system is often too expensive to be used repeatedly, for instance in optimization, uncertainty