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project focuses on developing ultra-reliable spatiotemporal (4D) predictions using trustworthy, distributed AI-driven intelligence deployed across heterogeneous aerial nodes. To achieve this, an aerial
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or damage. Along these lines, this project develops SHM methods for deep tunnels, with the HADES Underground Research Laboratory (URL) serving as the primary case study. The monitoring strategy combines in
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models. The project involves close collaboration with experimental facilities as well as simulation and condition-monitoring experts, ensuring a multidisciplinary environment. The project aims to develop
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candidates must thus have a strong interest in algorithmic development as well as embedded hardware integration. Role and responsibilities This PhD project will be executed in close cooperation with
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refer to https://www.uni.lu/snt-en/research-groups/sigcom/ . Your role The successful candidate will join the SIGCOM Research Group, led by Prof. Symeon Chatzinotas. This PhD project aims to develop
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new solutions for urgent problems. Those solutions will take the form of new constructs, models, and methods (i.e., algorithms and best practices). You will then develop prototype software
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aspects of theoretical chemistry. They will develop new approaches and algorithms for quantum chemistry and molecular dynamics, drawing inspiration from the opportunities offered by advances in quantum
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involved in the social and environmental transition, ULiège supports students to fulfil their roles as responsible citizens (training in sustainable development, Green Office, etc.) and promotes ethical
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their roles as responsible citizens (training in sustainable development, Green Office, etc.) and promotes ethical, multidisciplinary and open research. ULiège is committed to the region in which it operates
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eigenfrequencies, mode shapes, and modal damping ratios - can indicate structural changes or damage. Along these lines, this project develops SHM methods for deep tunnels, with the HADES Underground Research