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The Machine Learning for Integrative Genomics team at Institut Pasteur, headed by Laura Cantini, works at the interface of machine learning and biology, developing innovative machine learning
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be expected to teach advanced courses in Artificial Intelligence—particularly in machine learning, statistical learning, natural language processing (NLP), symbolic AI, computer vision, and related
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friction models. Integrating Experimental Data: Collaborate with experimental teams to incorporate data from calcium imaging, confocal microscopy, and high-resolution video recordings. Use experimental data
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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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Design and conduct analyses linking vocal biomarkers to validated psychological scales (e.g., PAID, PHQ-9, GAD-7). Apply natural language processing (NLP) and AI techniques to large-scale audio datasets
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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patient clusters and digital phenotypes, leveraging machine learning approaches to identify individuals at high CV risk based on clinical and biochemical markers, immune markers, digital health data (e.g
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number of techniques routinely used in the lab including histology, confocal microscopy and image processing. Prior expertise in cell culture, image analysis and coding would be highly appreciated. Part of
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Description of the offer : During this PhD thesis, we propose to explore the properties of exotic antiferromagnetism, in non-collinear antiferromagnets like Mn3Sn or in altermagnets. We will image
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used to develop networks capable of self-learning and self-optimisation, adapting to real-time changes in traffic and demand. The successful candidate will contribute to designing solutions that optimise