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Field
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. Understanding and controlling how energy is partitioned between hot-carrier generation and heat dissipation remains a central challenge in nanophotonics. This PhD project will address this challenge using two
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. The PhD candidate will combine materials science, computational modelling to design a novel framework that identifies optimal materials and AM processes based on performance, sustainability, and reusability
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incorporate optimized machine learning algorithms, support standardized IoT protocols, and be validated in laboratory and semi-industrial environments. The project contributes to smart maintenance strategies
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Centre de Mise en Forme des Matériaux (CEMEF) | Sophia Antipolis, Provence Alpes Cote d Azur | France | 16 days ago
of these microstructures, influenced by the nature of the materials and the welding parameters, is a major challenge for the future optimization of NDT methods. In this context, this PhD project aims to develop virtual
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, system optimization, flexibility management, and resilience analysis. The work will be carried out in close collaboration with our interdisciplinary teams at both Empa and EPFL, as well as external
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a strong background in computational modeling, optimization, and systems engineering, eager to develop advanced design and simulation frameworks for battery pack topology and e-powertrain integration
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. The project will involve the optimization of an experimental workflow, combining in vitro screenings, ex vivo tetramers staining, single-cell RNA sequencing and T cell receptor sequencing, to detect and
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prototype maritime AI solutions, the center will address a diverse and impactful set of use cases: Logistics, shipping and business transactions; Ship design and construction; Voyage planning and optimization
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are ready to embrace interdisciplinary research. Fluent command of English language is required. The 4-year project will be carried out in the state of the art laboratories (http://makrokomplex.cz
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compatible with high-speed imaging over long durations, (2) optimize system control and develop signal processing tools, and (3) apply it to imaging challenges involving organoids and living biological tissues