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prediction to process optimization. The focus of this PhD project is to develop and apply machine learning methods across three interconnected tasks: 3D microstructure characterisation. The student will
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, such as heterogeneity of data sources and communication constraints. By leveraging tools from statistical signal processing, machine learning, optimization, and mathematical modeling, the project aims
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particular connectivity within and between complex system? Would you like to apply efficient AI techniques for adaptive configuration and optimization of industrial communication networks to enhance
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involve the conceptual and practical development of the methodology for electrochemically initiated time-resolved soft X-ray spectroscopy, including construction and optimization of measurement setups and
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identification, optimization, or numerical methods is valuable, as is knowledge of data analysis and machine learning for complex, high-dimensional systems. Programming experience in MATLAB or Python, and an
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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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expertise from control theory, machine learning, optimization, and network science, spanning diverse application domains such as energy systems, biomedical systems, neuroscience, and safety and security
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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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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | about 1 month ago
Website https://jobs.inria.fr/public/classic/en/offres/2026-09839 Requirements Skills/Qualifications Strong mathematical background. Knowledge in numerical optimization is a plus. Good programming skills in
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dynamics. Particular emphasis is placed on opinion dynamics as well as distributed problems in coordination, optimization, and learning. The research encompasses both theoretical and computational aspects