16 10-phd-candidates-or-postdoctoral-researchers-in-machine-learning-and-deep-learning PhD positions in France
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exciting opportunities for machine learning to address outstanding biological questions. The PhD student to be recruited will be working on the development of machine learning methods for single-cell data
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candidate to undertake research in the area of cognitive networking for 5G/6G networks, with a focus area on connected and autonomous mobility. This research will explore how artificial intelligence can be
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the amyloidogenic potential of these candidates, in vitro protein aggregation assays will be performed. Your profile Early-stage researcher: a researcher without a PhD, who is in the first four years (full-time
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English. French is an asset. Training & Environment The selected candidate will be fully embedded in the Deep Digital Phenotyping Research Unit at the Department of Precision Health of the Luxembourg
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Artificial Intelligence (applied mathematics, computer science, etc.), or a thesis defense scheduled for 2025. • Research contributions in deep learning, statistical learning, natural language processing (NLP
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-on-chip platforms. 🤝 Why join us ? …. By joining the IRIG Institute, you will become part of a dynamic and innovative research environment where you will have the opportunity to learn, grow and play a key
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Grenoble Alpes (UGA) and the ESRF enabling the partners to combine their complementary expertise to deliver pioneering, high-impact research on these novel functional materials. The PhD student will benefit
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Description of the offer : The condensed matter theory group at Institut Néel (CNRS, Grenoble) invites applications for a three-year PhD position in condensed matter physics starting from October
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research and soft robotics development. PhD project The PhD project will focus on the technical aspects of simulating the physics of the Drosophila larva body. The primary objectives include: Developing a
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study and other ongoing translational initiatives to develop a voice-based digital health solution to alleviate the diabetes burden. Project objective The PhD candidate will work at the interface