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learning, epigenomic data, and mechanistic modelling. The mission is to contribute to the development of predictive models of the replication initiation probability landscape (IPLS) from limited experimental
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have skills in eukaryotic cell biology, electron microscopy, and bioimage analysis. You have a basic knowledge in integrative structural biology, and in AI / deep learning approaches and/or sub-tomogram
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, integrating statistical inference, machine learning, and population genetics. We will develop advanced computational methods to characterize the functioning of T- and B-cell repertoires. The goal is to build
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core mechanics (game design) Model the BDI (Beliefs, Desires, Intentions) agent system to be learned by the AI Program the game application specifically for mobile devices Evaluate the game's
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core mechanics (game design) Model the BDI (Beliefs, Desires, Intentions) agent system to be learned by the AI Program the game application specifically for mobile devices Evaluate the game's
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motivated candidate with: a PhD in immunology, with expertise in T cell/B cell interactions and/or vaccinology an expertise in advanced flow cytometry a strong motivation to learn organ-on-chip technologies a
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the interface of machine learning and biology, developing innovative machine learning methods for single-cell data analysis (tools developed by the team: https://github.com/cantinilab). Single-cell high
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core mechanics (game design) Model the BDI (Beliefs, Desires, Intentions) agent system to be learned by the AI Program the game application specifically for mobile devices Evaluate the game's
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Disease. As a postdoctoral researcher in our lab, you will have the opportunity to work on cutting-edge research projects related to glial cell function and cognitive behavior, using a variety of techniques
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challenges in stem cell research, aging and disease modeling. The group employs methodologies from different areas of mathematics, engineering, and physics, and integrates multiple sources of biological