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Field
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-supervision by a doctor and a statistical/machine-learning researcher is planned (iBV / Inria) 1- Context and Objective: Monitoring tumor response using clinical imaging, such as CT or FDG-PET, has become a
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/CT imaging Description of the topic As this is an interdisciplinary "AI and medicine" project, co-supervision by a doctor and a statistical/machine-learning researcher is planned (iBV / Inria) 1
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advances in machine learning and data-intensive approaches facilitate the search for better or even global minima via evolutionary computations or reinforcement learning. Objectives. The main scientific
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centre at Universit´e Cˆote d’Azur, I3S Lab (Universit´e Cˆote d’Azur and CNRS) in collaboration with the Machine Learning Genoa Centre (MaLGa) at the University of Genova (Italy). The candidate will be
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Angelopoulos, Stephen Bates, et al. Conformal prediction: A gentle introduction. Foundations and Trends® in Machine Learning, 16(4):494–591, 2023. Arthur P Dempster, Nan M Laird, and Donald B Rubin. Maximum
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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
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train robust machine learning (ML) algorithms without exchanging the actual data. The benefits of such a decentralized technology over personal and confidential data are multiple and already include some
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toxicities. The proposed thesis aims to extract biomarkers that are predictive of the response to targeted therapy for patients with KRAS-mutant non-small cell lung cancer. To this end, machine learning
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of specialized deep learning models (neural network or transformer) for automated segmentation of tibial plateau fractures. iii) The algorithm must then be trained to allow it to learn the morphologies of bone
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approaches (e.g., GANs [2] or Plug& Play [3]). A different and increasingly popular class of methods producing outstanding results in many applied fields is based on the use of modern generative learning