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approach and framed as a continuous improvement process, and (3) on machine learning algorithms guided by theory and analogues from natural objects and simulations. The proposed position will cover four
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of learning dynamic systems and physically informed neural networks (PINNs), for application to neuroscience research. The main task of the postdoctoral fellow will be to develop models for modeling
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approaches for multivariate Climate Extremes modelling. To identify and exploit applications of Machine Learning to extreme values. To produce scientific material (papers/articles, conferences, seminars
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related to staff position within a Research Infrastructure? No Offer Description [Technical] Assist the team with computer resources (access to clusters, and scaling machine learning programs), [Technical
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, deep learning-based image methods have emerged as a prominent tool in medical image processing. While they have shown impressive success in various computer vision tasks, their application in the medical
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or as materials for transportation. Intensive calculations within the framework of density functional theory (DFT) will provide the basis for building machine-learning models to explore the range
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the development of Danionella fish. Activity (and possibly behavioral) recordings will be combined with computational approaches combining statistical physics and machine learning to track the evolution
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global approaches capable of describing fission across the entire nuclear chart 3) new approaches based on machine learning techniques. Applications will focus on the area of the nuclear chart reached by
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Optics (cacao), and runs on a real-time Ubuntu computer. The Postdoc will join the Apollon facility's operations team and will be responsible for operating, maintaining, and expanding the capabilities
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(https://www-ipcms.u-strasbg.fr/stmipcms/ ). These two teams currently comprise five permanent staff members, two engineers, 4 PhD students, 2 Postdocs and Several MSc interns. In addition to the subject