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decisionmaking modules that must operate under strict constraints on latency, compute, energy, and reliability. In many robotic platforms (mobile robots, drones, autonomous vehicles, ...), inference must execute
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-world medical use case to validate the long-term application of Quantum Key Distribution (QKD) and Post-Quantum Cryptography (PQC) in operational hospital environments. The project represents a major step
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the exact calculation of the square-root and inverse square-root of the source distribution covariance matrix. This approach offers analytical and computational advantages in comparison to existing methods
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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of several researchers working in the field of inverse problems due to their ability of combining variational inference approaches with the ability of neural networks to learn unknown posterior distributions
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. Processing this response provides estimates of the local variations in acoustic pressure along the fiber, over distances ranging from 40km up to 140km with some systems. This technique, called Distributed
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The candidate should preferably have a PhD in Computer Science or Robotics with a solid background on deep learning and 3D scene understanding. Experience with LiDAR and Computer Vision is a plus. The candidate