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The SiMul team (https://cran-simul.github.io) at the University of Lorraine is offering a fully funded PhD position on the theoretical foundations of self-supervised learning, focusing
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Mines Paris - PSL, Centre PERSEE | Sophia Antipolis, Provence Alpes Cote d Azur | France | about 2 months ago
through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Title: "Decision-Focused Learning
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problems. This level of complexity increases when considering the multi-period operation of the system. These are difficult to solve using traditional strategies, so in recent years machine learning
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-correction. This PhD falls into the fields of error-correction and Deep Learning. Due to the inherent unreliability of the DNA storage support, the goal will be to develop advanced deep learning models
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, where innovative ideas and scientific advances are encouraged and valued. Federated learning (FL) is a promising paradigm that is gaining grip in the context of privacy-preserving machine learning
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, data scientific or machine learning background that is keen to work in an interdisciplinary environment and open to collaborating with researchers from other disciplines. The successful candidate will
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of the project is to use machine-learning assisted molecular dynamics simulations incorporating quantum effects for the identification of new variant-specific drug targets which will be validated experimentally
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protection of scientific and technical potential (PPST), and therefore requires, in accordance with the regulations, that your arrival is authorized by the competent authority of the MESR. Federated learning
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the field of algorithm configuration and selection in a streaming fashion by investigating techniques that continuously optimize machine learning models as new data instances arrive [2]. A key focus will be
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behaviour using computational approaches such as Bayesian program synthesis and inverse reinforcement learning. Investigate the diversity of motor commands that could implement observed behaviours and explore