55 algorithm-development-"the"-"The-Netherlands-Cancer-Institute"-"UCL" positions in France
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for simulating such complex geometries. For example, the memory and computation time required become prohibitive with standard “black-box” finite element methods. The objective is therefore to develop a dedicated
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des Fluides et d'Acoustique - LMFA) develops a continuum of research in fluid mechanics and acoustics, from the understanding and the modelling of physical phenomena to applied research, in
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an internationally recognized research team at LAAS-CNRS in Toulouse, focused on developing autonomous mobile machines that integrate perception, reasoning, learning, action, and reaction capabilities
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interdisciplinary, and together we contribute to science and society. Your role Multi-omics data integration and workflow improvement Development and application of machine learning-based algorithms
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techniques and the structure of bilevel problems in large-scale settings. Objectives The goal of this postdoctoral project is to develop scalable blackbox optimization algorithms tailored to bilevel problems
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proof of excellence in teaching. They should show expertise in their specific area and experience in Data Science and/or Software development, including academic publications and contributions
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identify optimal or near-optimal solutions. To address these challenges, CEA has developed A-DECA (Architecture Design Exploration and Configuration Automation), an in-house Electronic Design Automation (EDA
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behaviours. Various methodologies have been developed, including physics-informed ML approaches that use numerical modelling to create synthetic datasets (e.g. Tristani et al., 2025). Additionally, approaches
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and interpretation. Prominent examples include time sequences on groups and manifolds, time sequences of graphs, and graph signals. The objectives The project aims to develop unsupervised online CPD
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the development of more efficient online learning algorithms for manifold-valued data streams, with an initial focus on change-point detection, opening the door to new unsupervised data exploration methods. Next