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research work will be to devise efficient algorithms for source separation in DAS measurements. Issues such as large data volumes that can exceed 1 To per day and per fiber, instrument noise, complex nature
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slicing. - Develop advanced AI/ML algorithms and data analytics techniques to automate and optimise exposure requests, adapted to available resources and real-time demand. - Propose and
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analyzed. The tensor model structure estimated by suitable optimization algorithms, such as that recently developed in [GOU20], will be considered as a starting point. • Exploiting data multimodality and
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(morphological patterns), based on the experts’ knowledge. Then, tools like Procrustes analysis, linear dimensionality reduction (PCA) and standard clustering algorithms are employed. A first objective of our
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the use of synthetic data in precision medicine research and applications through development of AI algorithms, tools and other processes to allow for the enrichment of clinical data sets Providing training
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shared with the broader scientific community. As the head of the Algorithmics, AI, and Mathematical Modeling group within the Bioinformatics and Biostatistics Hub, the recruited engineer will focus
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that shape the design of these circuits. The lab is dedicated to medical algorithmics on the applied research front, emphasising technologies implementable within hospitals. Notably, the lab’s medical image
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of the surgical procedure (direct filming and arthroscopic video feed), and a device for recording heart rate. In the second phase, the student will propose signal processing and data fusion algorithms to reconcile and