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on the flow in soap films and will help us better understand how surface viscosity affects foam drainage, bubble coalescence, and the aging of fluid interfaces. Where to apply Website https://emploi.cnrs.fr
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Description This is a fully funded PhD position for 3 years (2300 € (gross) per month) supported by the PEPR DIADEM program. The PhD candidate will be recruited in the framework of the AMMETIS (AI-assisted
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that give rotaxanes the ability to produce reactive oxygen species, and applications of these architectures in antibacterial photodynamic therapy. Where to apply Website https://amethis.doctorat.org/amethis
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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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practices, and the growing popularity of free-range farming. As such, characterising the interface in various settings may help to predict future trends in infectious disease risk. In three study sites with
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cardiovascular disease, chronic kidney disease, cancer and chronic inflammatory disease. For more information: https://www.cordis.europa.eu/project/id/101225380 Cardiovascular disease (CVD) is the leading cause
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is accessible online: https://www.tec21.fr/phd-tec21 What we offer : 7 fully funded PhD positions with employment contract, competitive salary (monthly estimate net salary between 2 050 and 2 150 EUR
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project. Specific or cross-functional activity: Cross-functional contribution to a project on transformative marine changes on the African continent and assistance with project management. Faced with
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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | about 2 months ago
efficient computational framework. The selected candidate will be able to collaborate closely with experts who will help guide the research direction. This work will contribute to the broader objective
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, the candidate will help the team on the following tasks and research areas : - improve integration of the framework with learning/inference framework (PyTorch, Keras, AIDGE, ...) - improve implementations of low