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between complex instances such as point clouds, images or graphs. However, as the modern data are increasingly high-dimensional, OT is also now facing an old problem in optimization and statistical learning
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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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-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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a challenging problem. Candidate profile PhD on optimization and/or image processing. Strong background in applied mathematics, image processing, learning methods and algorithms. Good coding skills
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Master/engineer degree in computer science, applied mathematics, data science with background in image processing, imaging inverse problems, deep learning and optimisation. Good coding skills for numerical
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opportunity for an outstanding scientist to establish an independent research program at the interface of biology and computer sciences, in one of the five major DYNABIO-affiliated institutes (C3M, iBV, IPMC
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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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. Required Skills and Candidate Profile The project is intended for a candidate with: ➢ Skills in medical image processing and deep learning adapted to clinical applications. ➢ A good knowledge of Python
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computation of visibility for the whole domain is intractable due to its high computational complexity, we will explore leveraging machine learning techniques such as reinforcement learning for the efficient
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activity can be considered. Teaching portfolio: The holder of this position is expected to co-build, co-direct, and teach in the bachelor's programme in medical imaging technologies and related fields. He