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: - Apply unsupervised machine learning concepts to the analysis of continuous seismograms recorded in the vicinity of active volcanoes, in order to extract information about the state of the volcano and the
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professors, teacher-researchers, engineers, and doctoral students. The team is mainly involved in the PALLAS laser-plasma accelerator project. Optimizing Laser-Plasma Accelerators through Machine Learning The
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specialized in Technology-Enhanced Learning (TEL) and Human-Computer Interaction (HCI). In particular, SICAL has extensive experience in behavior analysis using multimodal data in different contexts, including
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controlling these molecular networks in vivo . This will be achieved using scRNAseq, spatial transcriptomics, advanced machine learning approaches, and genetic approaches to manipulate the expression of
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in the field of medical imaging. The team particularly studies the potential of machine learning methods for an efficient and relevant representation of medical data such as images. The challenges
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machine learning, speech science, cognition and behavioural studies. If all disciplines are addressed in this PhD position, candidates without expertise in some of the areas listed below are nevertheless
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is an impossible task in metasurfaces composed of millions of elements. The PhD aims to develop methods using machine learning surrogate models to solve this complex design problem. The project aims
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friendly refrigeration [1]. To do so, this PhD aims to develop original modeling methods, based on the development of Machine Learning tools, allowing for the description of complex molecular systems
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the Subatech team is one of the pioneers, to control associated errors and biases. Similarly, we will continue exploring innovative deep learning methods emerging from pioneering work within this team
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Ifremer - French Research Institute for Exploitation of the Sea | Plouzane, Bretagne | France | about 1 month ago
and biology Good knowledge of machine learning methods (e.g. Bayesian networks or Machine Learning, neural networks) Good modeling and programming skills (e.g. Python, R, Fortran, C++). Proficiency in