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environmental impact of cloud infrastructures. Context and Motivation The deployment of AI applications is undergoing a paradigm shift with the advent of 5G/6G networks, the Internet of Things (IoT), and edge
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eNSEMPLE. It is an interdisciplinary project at the interface between Statistical Physics, Data Science, Network Science, Computer Science and Sociology, and will involve collaborations with researchers from
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. However, one of their major limitations is their moderate ionic conductivity. A promising approach to circumvent this issue is to incorporate other network formers than P, such as Si or B. Nevertheless, our
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-Curie doctoral network Recruited researchers will be part of the EURECA doctoral programme, which offers: - A thorough scientific education within a structured doctoral training programme. - The
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The postdoctoral researcher will join the "Network Dynamics & Computations" team led by Srdjan Ostojic and develop research projects on modeling neural circuits and their role in behavior. The work will focus
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and one year at the other institution. Scientific Context and Originality Traditionally, congestion management relied on preventive planning, redispatch, and curtailment under fixed network topologies
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maintaining national networks of geophysical instruments, and by operating a data center. The thesis will be conducted within the Waves and Structure Team, under the supervision of Nikolai Shapiro and Laurent
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implement and train neural network architectures, including Physics-Informed Neural Networks (PINNs), in order to integrate physical constraints into the learning process and improve the identification and
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confined vascular networks. The project aims to understand the coupled roles of fluid shear stress and confinement on adhesion dynamics, mechanical adaptation, and metastatic potential, by combining
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a vast network of national and international collaborators (including the University of North Carolina and the University of Vienna), offering the candidate real opportunities for mobility (funds