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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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experimental campaigns to acquire the data required for his thesis, as well as for the MONI-TREE project as a whole. The PhD will take place in LETG-Rennes, with expected missions to ONERA's Palaiseau for works
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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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at EM2C lab, which consists in introducing virtual species and reactions whose thermodynamic and chemical properties are optimized by machine learning algorithms to retrieve properties of reference flames
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. Fujii, K. & Nakajima, K. Harnessing disordered-ensemble quantum dynamics for machine learning. Phys Rev Appl 8, 024030 (2017). 2. Rudolph, M. S. et al, Generation of High-Resolution Handwritten Digits
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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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physics or computer science, with a solid background in AI/machine learning techniques. A background in plasma transport phenomena as well as an experience with data analysis, statistical methods, and
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materials or molecular modeling and will have skills in algorithmic programming (python required, C++ would be a plus). Experience in the field of machine learning will be appreciated. Additional comments