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look forward to receiving your application! Do you have a background in machine learning and interested in telecommunications? You have a chance to contribute to development of sensing methods for new
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availability. Funds are available to support conference travel and professional development. Duties & Responsibilities: • Successful candidates will develop and refine computational, mathematical, and
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, transfer learning, federated learning, data integration, algorithmic fairness, survival analysis, and methods for heterogeneous and multi-source data. Training Environment and Career Development
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of this thesis focus on several key areas: - Detection and modeling of node mobility: Supervised learning models will be developed to identify mobility patterns based on radio indicators such as RSSI, SNR, and
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Les estimateurs sécurisés sont des algorithmes qui exploitent la
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candidates will have specialist knowledge in signal processing and algorithm design, with experience in machine learning, AI system development and reinforcement learning along with a strong publication record
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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validation (V&V) techniques for space systems, software and algorithms with a focus on specific challenges of space-borne perception and proximity operations uncooperative spacecraft . Develop novel methods
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, the CSATLab , our SW Simulators , and our Facilities . For further information, you may refer to https://www.uni.lu/snt-en/research-groups/sigcom/ . Your role Develop innovative methods and data-driven AI tools
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Framework Programme? Not funded by a EU programme Reference Number 173095 Is the Job related to staff position within a Research Infrastructure? No Offer Description CASTRO aims to develop wireless signal