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to the large-scale nature, complexity, and heterogeneity of 6G networks, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal
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advancements and practical implementations optimized for modern HPC systems. The postdoc will primarily contribute to one or more of the following research areas: Development of efficient numerical linear
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, United States of America [map ] Appl Deadline: (posted 2025/09/04, listed until 2026/02/20) Position Description: Apply Position Description Postdoctoral Associate – Scientific Machine Learning for Multiscale Biological
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, their modelling through mathematics and numerical simulations, and their control and optimization. Our belief is that a proper understanding of systems requires a modelling step, which allows to identify causal
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ocean environments, ensure safe and sustainable operations. Our activities are centered on numerical modelling (e.g. CFD, FEA, FSI, optimization, machine learning), but also include experiments and real
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inflow reconstruction techniques for lidar-assisted control and load assessment/validation. Contribute to the development and modelling of wind turbine control methods with the aim to optimize wind turbine
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testing, and advanced process simulation, with the objective of optimizing grinding performance and enhancing resource recovery. The ideal candidate will have a strong background in mineral processing
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solution; Activity 3 - Development of numerical prediction tools and models; Activity 4 - Parametric studies, analysis, and optimization of solutions; Activity 5 - Production of prototypes for experimental
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performance of optimized industrial formulations; Computational simulation of materials and solutions using numerical methods; Preparation of reports and scientific papers for the dissemination of results. V
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teams to integrate AI and machine learning techniques into lattice field theory frameworks. - Engage in large-scale numerical simulations, performance analysis, and optimization using state-of-the-art