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recruited candidate will contribute their expertise to the initial training of engineering students and master's students by teaching in the following areas: • Bioinformatics, • Machine learning and pattern
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comprehensive platform for data extraction, analysis, and version control, providing access to highly curated datasets in a machine learning-friendly format. This PhD is part of the CARES project (Chemically
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Technologies de l'Information et de la Communication Field: Telecommunications / Machine Learning / Statistical Signal Processing. Research Lab: L2S (Laboratoire des Signaux et Systèmes) Advisor: Antoine BERTHET
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, Jianmin Wu, Use of porous silicon-gold plasmonic nanostructure to enhance serum peptide signals in MALDI-TOF analysis. Analytical Chimica Acta, 849, 27-35, 2014. Oliver T. Unke et al. Biomolecular dynamics
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French National Research Institute for Agriculture, Food, and the Environment (INRAE) | France | 3 months ago
. Regarding the analytical aspects, you will collaborate with the partner proteomics and metabolomics platforms. By adding to the datasets already available, you will be able to select candidate proteolytic
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collaboration between the Exa-SofT and the Exa-DI projects and better support multi-linear algebra and tensor contractions in exascale CSE applications and Machine Learning. As part of the collaborative process
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learning community. Basically, once the observed data is identified with a probability distribution (possibly the empirical mass function), optimal transport allows to consistently assess the similarity