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data integration. · Familiarity with machine learning methods (e.g., classification models, dimensionality reduction, clustering). · Experience analyzing epigenomic data · Prior work in hematologic
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. The ICN has a background in knowledge graphs representation and processing for mass spectrometry and metabolomics. The Wimmics team specializes in different AI techniques for knowledge graph providing open
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of GPP (gross primary production) to a nutritional stress for K (Cornut et al., 2022) The overall objective of this postdoc project is to improve our knowledge of nutritional dynamics in forest ecosystems
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-performance computing. It aims to improve the performance of the matrix-free finite-element-based framework HyTeG, in particular by techniques for data reduction through surrogate operators. Furthermore, we aim