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objective will be to develop algorithms for predicting and planning the evolution of local energy systems (microgrids) over a time horizon of several years, using machine learning and numerical optimization
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mechanical activity at the same time. In this context, the use of mathematical models and machine learning methods can be relevant to integrate physiological knowledge in data analysis and to analyze
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available1Company/InstituteInriaCountryFranceGeofield Where to apply Website https://illbeback.ai/job/phd-position-f-m-machine-learning-for-efficient-bimoda… STATUS: EXPIRED
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statistics Excellent background in statistical/machine learning Experience in computer vision is a plus Strong motivation for medical and societal applications of computational methods Knowledge of biology and
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Research Framework Programme? HE / MSCA Marie Curie Grant Agreement Number 101120240 Is the Job related to staff position within a Research Infrastructure? No Offer Description Machine Learning for Quantum
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models validated in WP3 will be implemented in the free TDMx software. What we offer The future PhD student will benefit from the expertise in pharmacometrics and machine learning of Profs Grégoire and
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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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PhD offer in Channel charting and machine learning techniques for massive cell-free MIMO 6G networks
programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Title Channel charting and machine learning techniques for minimizing the power consumption of massive
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of this PhD research is to develop novel optimization strategies for laser-plasma accelerators through the application of machine learning algorithms. Laser-plasma accelerators offer tremendous promise for
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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