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biological signals. The project will focus mainly on developing innovative models for biomedical signals with irregular cyclicity and exploring potential machine learning applications. Position Objective
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in the Earth's outer core, with implications for deep Earth processes [1]. A variety of inverse methods (data assimilation, machine learning, etc.) has been employed to recover the fluid motions in
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of the project is to exploit such data to develop generative models for aptamer design. The candidate is expected to have a strong background in machine learning and statistical physics, with a real interest for
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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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, Python, Bash). Good level on machine learning. Good level of written and oral English. Ease in a multidisciplinary environment, taste for teamwork, interpersonal skills. Scientific curiosity