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Research Framework Programme? Horizon Europe - ERC Is the Job related to staff position within a Research Infrastructure? No Offer Description The Machine Learning for Integrative Genomics team (https
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- python programming Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR8214-SANLEV-038/Default.aspx Work Location(s) Number of offers available1Company/InstituteInstitut des Sciences
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Sorbonne Université SIS (Sciences, Ingénierie, Santé) | Sophia Antipolis, Provence Alpes Cote d Azur | France | 12 days ago
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Postdoctoral researcher (M/F). Modeling damage during earthquakes. Comparison with geophysical data.
. Use of digital earthquake models; The code used for calculations is written in Fortran, and the tools for processing input and output data are written in MATLAB and Python. The postdoctoral researcher's
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% with Laura Cantini’s team and 20% with the Bioinformatics and Biostatistics HUB. Information about the teams : The Machine Learning for Integrative Genomics team : https://research.pasteur.fr/en/team
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). Conduct in vivo optical imaging experiments on healthy volunteers and patients; Develop image-analysis pipelines (Python, MATLAB) and model functional optical signals; Optimize and maintain the AO-RSO
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transcriptomics data and network-theoretic approaches. - design of a new mathematical method - monitoring and study of publications relevant to the field - programming/coding in Python (Pytorch) - presentation
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Team : We seek a researcher with demonstrated experience in perturbative modeling of LSS (in particular biased tracers of dark matter), analysis of simulated datasets, and strong programming in Python
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Programme (PEPR) Forest Resilience (FORESTT – https://www.pepr-forestt.org/ ), funded by the French Plan d'Investissement d'Avenir (PIA) France 2030. FORESTT aims to support the transition of forest socio
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, brings together around 300 people and is one of the leading centers for fundamental research in biology in the Paris region. The host team (https://www.ijm.fr/recherche/duharcourt-lab-vf/ ) is particularly