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. The PhD will employ a combination of simulation and experimental validation. First, use and develop existing coronagraphic simulation tools in python to develop innovative algorithms, then conduct tests
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turbine blades. Successful re-development for end-of-life composites could enable reuse in other structural applications. This PhD will investigate the development of hierarchical Bayesian algorithms
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will develop and evaluate fault detection and fault location algorithms for these systems. The project is funded by GE Vernova under a wider collaboration with Imperial College London. You will be co
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transmission of information and energy, systems theory, and computational hardware and software. ECE students are encouraged to develop synergies with disciplines outside of engineering. The candidate should
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for Research in Mathematical Sciences and the Principles of Intelligence (PrincInt: https://princint.ai/ ), housed within the Fields Institute's Centre for Mathematical AI. The fellowships support research
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, funded by the ANR P2S2 project. The position is available initially for a fixed-term duration of 2 years, with the possibility of extension for 1 further year. The P2S2 project aims at developing parton
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wireless communications systems. For details, you may refer to the following: https://wwwen.uni.lu/snt/research/sigcom We’re looking for people driven by excellence, excited about innovation, and looking
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, including deep reinforcement learning, large language models, and the theory of deep learning. The candidate will develop DRL algorithms for online and off-line tasks, for robotic applications and possibly
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(Task T2.4). Implement algorithms for training with limited data (Task T3.1). Develop prototypes for use cases in Smart Cities (Task T4.3). These tasks are part of the IDEALCV-CM project, reference: TEC
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of this PhD project is to develop machine learning algorithms that perform efficiently and coherently across both classical and quantum computing platforms. The PhD project falls under the collaboration between