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Field
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scienceEducation LevelPhD or equivalent Skills/Qualifications PhD in computer science Background in probability, Markov chains, MDPs Knowledge about reinforcement learning and planning are a plus but not necessary
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. • Strong knowledge of signal processing methods and machine learning. • Familiarity with regulatory and ethical constraints in research involving sensitive data. • Ability to work closely with
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of machine learning algorithms are of real interest in improving the accuracy of water quality measurements, particularly in identifying, accounting for, and neutralizing ionic interference. The second key
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perception for robotics; machine learning. o An interest for approaches based on foundation models. o Proficiency in open-source libraries: Pytorch or equivalent, OpenCV, Open3D, PCL, etc. o Programming
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resonance spectroscopy, imaging (MRI), Applied Mathematics or Machine learning. We are looking for talented, highly-motivated experimentally skilled young scientists with Master degrees or equivalent or PhD
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relevant to the project's theme and activities. Solid experience in molecular simulation and/or machine learning is required, along with a good knowledge of associated theoretical tools (experience in
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on food craving and health-related decision-making. To this purpose, we will use a combination of brain imaging, behavioral measures, and machine-learning techniques. Activities The successful candidate
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by exploiting foundational machine-learning potentials such as MACE, SevenNet, or Orb-V3. The predictions will then be progressively refined and verified by DFT and, ultimately, tested experimentally
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machine learning. We particularly value depth of knowledge, originality, and the potential for cross-disciplinary innovation. Relevant application areas may include (but are not limited to) natural
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of the mines must also be considered. Recent advances in the geotechnical and geomechanical fields have led to a significant increase in the usage of machine learning (ML), thanks to its computational power and