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disease, systems biology (including the modeling of signaling pathways and biomolecular structure-function relationships), and stochastic modeling of disease processes such as progression, detection, and
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of metabolic and cellular properties Phylogenomic analyses of obtained MAGs, including extraction and evaluation of marker genes, performing ML and Bayesian analyses of (concatenated) marker gene sets using
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candidates with strong expertise in Bayesian methods, uncertainty quantification, and/or machine learning applied to nuclear theory. The group’s research spans a wide range of topics including nuclear
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forecasting. Familiarity with ensemble methods, Bayesian approaches, and uncertainty estimation. Experience with large-scale or messy real-world data (structured and/or unstructured). Interest in or experience
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 3 months ago
algorithms able to provide decision making in uncertain environments. He was PI of several projects, including ANR-JCJC project BADASS (BAnDits Against non-Stationarity and Structure), Inria Action