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with deep-learning, UniGEM aims to build a neural network to estimate epidemiological parameters of P. falciparum, the deadliest malaria parasite species (read [1] to learn more about the ideas behind
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The Machine Learning for Integrative Genomics team (https://research.pasteur.fr/en/team/machine-learning-for-integrative- genomics/) at Institut Pasteur, headed by Laura Cantini, works at
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susceptibility to foodborne TBE using mouse models. Learn more about our lab: https://research.pasteur.fr/en/team/mouse-genetics-immunity-and-infections/ Project: Identification of host genetic factors controlling
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+ DCs (DC2As, DC2Bs, DC3s) and plasmacytoid DCs (pDCs and pDCs-like). Some DCs can uptake LNPs and express LNPs (direct presentation), acquire antigen form other cells (cross-priming) or even acquire MHC
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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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, 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
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with machine learning approaches Knowledge of muscle mechanics (Hill muscle model or similar) Previous work on simulated bodies or animal locomotion Your Role You will work collaboratively with a