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Field
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. The projects will also focus on applications and algorithms employing X-ray scattering models to uncover spatiotemporal correlations in ultrafast phenomena, particularly fluid dynamics, studied at the recently
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, TensorFlow) and Python ML libraries (e.g., NumPy, OpenCV, scikit-learn). Experience implementing and evaluating state-of-the-art tracking algorithms such as DeepSORT, ByteTrack, and Transformer-based
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implementing and evaluating state-of-the-art tracking algorithms such as DeepSORT, ByteTrack, and Transformer-based approaches. Proven ability to design and run rigorous experimental frameworks, including
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this short-term project we shall use active learning to accelerate the training of deep learning algorithms for optimising 2D material van der Waals (vdW) structure discovery. The goal is to make model
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components: - operational modal analysis to extract the modes of the probed medium, - algorithmic and experimental developments on the MSE method - and algorithmic and experimental developments on the MFP
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learning, and generative AI Design and implement algorithms for quantum-inspired and quantum-enhanced generative models Investigate theoretical foundations of tensor networks, entanglement, and collapse
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(terrestrial and NTN). The goal of this research is to design and develop algorithms and techniques that adapt to the environment, minimizing signaling overhead associated with channel estimation and enhancing
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· Carry out research activities under the Department's contracts in the RS2M field · Participate in and ensure the delivery of project deliverables · Design and develop models, algorithms, and
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particle (SEP) events. The project is a joint collaboration of Algorithmics and Computational Intelligence research group at the Department of Computing and Space Research Laboratory at the Department
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Location: Luxembourg, Luxembourg 1511, Luxembourg [map ] Subject Area: Quantum LDPC codes with efficient decoding algorithms Appl Deadline: none (posted 2025/08/05) Position Description: Apply Position