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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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: - 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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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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research colleagues, and to learn about the larger context of my research and the research project. Offer: The aim of this PhD research is to optimize acoustic metasurfaces of finite size using machine
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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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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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spirit, and an ability to work in autonomy are essential. Fluent English both spoken and written is required The candidat must have a PhD in computer science, machine learning, or computational biology The
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advances obtained on Graph Neural Networks, on both convolution [5] and pooling [6] steps. 1.2 METHODOLOGY AND WORK PLAN The proposed PhD research program aims to develop innovative graph machine learning
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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