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of Learning and Development (LEAD- UMR-5022), at the Université Bourgogne Europe, CNRS (https://lead.ube.fr/ ) . To apply, please submit: - CV - Cover letter describing your interest in the position
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-machines and nano-robots as a drug delivery vehicles. As a core research activities, the postdoc candidate activities are the: - Design and in silico modeling of DNA origami nanostructures with high
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Candidates must have expertise in at least two of the following areas: • Machine learning and its associated mathematical foundations • Embedded systems • Analog / mixed-signal design Website for additional
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Vision Profiler (UVP), and to analyse its spatial and temporal variability. This will be done by combining different data sources and machine learning (ML). Data used for this ML approach include - a
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Technologies INspiring Young scientists (DESTINY2, https://www.destiny-phd.eu/ ) is opening 24 doctoral positions hosted by universities, research centres, and laboratories in France (17), Spain (3), Germany (1
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researchers with ample experience in MEG/EEG data analysis, BCIs, signal processing, deep learning for brain imaging analysis, biomedical statistics, dynamical systems and research on motor control. The lab has
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on studying the principles of neural computation through recurrent neural networks, dynamical systems theory, and machine learning. - Develop mathematical and computational models of neural networks - Analyze
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at least two of the following areas: Machine learning and associated mathematical foundations Embedded systems Analog/mixed design [1] https://emergences.pepr-ia.fr [2] https://www.frontiersin.org/articles
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-temperature-superconducting (HTS) magnets for the machine–detector interface of the FCC project, within the “Accelerator R&,D” group at LAPP." Where to apply Website https://concourschercheurs2026.dsi.cnrs.fr/index.php
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computer scientist with experience in bioinformatics, solid programming skills and knowledge in 3D protein structures. Machine learning skills and knowledge of Web development are a plus. Good interpersonal