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will be using metabarcoding for the analysis of microbiomes from field and greenhouse experiments, and you will integrate data on microbiome composition, nematode infestation, plant performance, plant
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modification. By marrying first-principles theory – trade-off analysis, game theory, reaction-diffusion, and consumer-resources models – with single-cell tracking and synthetic community experiments
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experience in the analysis of metagenomics and/or biological high-throughput data Knowledge of statistical and machine learning methods in the context of biological systems Experience with programming (e.g
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design based on stakeholder interaction model-based analysis of various technology and policy solutions participation in project meetings presentation of results at international conferences publication
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for the analysis of the sequence data, to describe the genetic diversity between French regions for different types of variants (SNV, indels, SV, STR, mictochondrial…). He/she will work in collaboration with our
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. The overall goal of the project is to design a novel high temperature heat pump. You will be conducting Computational Fluid Dynamic (CFD) simulations and cycle analysis, which will be instrumental
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to follow this initial post. Applicants should hold a PhD (or equivalent) involving neuroimaging, cognitive neuroscience or a related field. Experience in MEG/OPM-MEG acquisition and data analysis is
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Stage (MIS) 7 Publish key results in international journals and present them at scientific meetings Your qualifications: Master`s degree (or equivalent) and a PhD degree (or equivalent) in the (bio
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skills in data analysis, machine learning, as well as in mathematical and computational modelling? You will have the opportunity to investigate innovative solutions using machine learning algorithms and
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analysis with practically motivated case studies, offering a strong foundation for researchers interested in advancing the mathematical understanding of geometric deep learning. Your Qualifications PhD