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the BENEFIT project, funded by the French National Research Agency (ANR), to work on active flow control and machine learning. 1- CONTEXT -------------------- Active flow control aims to modify velocity fields
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opportunities for machine learning to address outstanding biological questions. The PhD (M/F), to be recruited in the context of the ERC StG MULTI-viewCELL, will be working on the development of a new method
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the "Machine Learning and Gene Regulation" team led by William Ritchie, specializing in bioinformatics and post-transcriptional regulation. The scientific environment at the IGH — international seminars, journal
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candidate will hold a PhD in geosciences, applied machine learning, data assimilation, or applied mathematics. The selection will be based on the following scientific and technical criteria: Experience in
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new thermoelectric materials using data science and machine learning methods applied to materials, based on expert-reviewed experimental data from the literature and public databases (notably
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, soil, and plants aid in the collection of real-time data directly from the ground. Based on these historical data predictive machine learning (ML) algorithms that can alert even before a problem occurs
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or Phonetics Basic knowledge of machine learning tools; familiarity with a scripting language Ability to communicate and coordinate with different partners: field linguists, computer scientists, engineers