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- Inria, the French national research institute for the digital sciences
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appointment. Job duties Mentoring new PhD students in numerical computational projects. Conducting comprehensive literature reviews in machine learning for subsurface flow and well performance and supporting
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machine learning and AI methods to develop clinical decision support systems for high-flow nasal cannula therapy. The project: Concerns around the possible negative consequences of delayed escalation
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machine learning-driven digital twins for predictive combustion modeling. The research program will cover a wide range of e-fuels (H₂, NH₃, CH₃OH, DME, OME) and their applications in industrial furnaces
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 2 months ago
into resources that can be used for machine learning. The PhD will therefore investigate multimodal approaches that connect visual sign-language information with textual representations under low-resource
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, machine learning, explainable artificial intelligence (XAI), digital twins, and integrated data-model approaches. • Study of the frugality of the developed approaches by reducing the requirements
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University of Girona (UdG) - Institute of Computational Chemistry and Catalysis (IQCC) | Spain | 2 months ago
next-generation computational approaches to understand, predict, and engineer highly reactive intermediates in enzymatic catalysis. By combining quantum chemistry, molecular dynamics simulations, machine
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
., Revenko, A., Teije, A. T., & Harmelen, F. V. (2023). Combining Machine Learning and Semantic Web: A Systematic Mapping Study. https://doi.org/10.1145/3586163 [2] Benoît Combemale, Pascale Vicat-Blanc
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the structural and electronic properties of complex materials. Using first-principles simulations, machine learning techniques, and advanced Monte Carlo methods, the student will develop predictive
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references: Ajay K. Agrawal, Joshua S. Gans, and Avi Goldfarb. 2019. The Economics of Artificial Intelligence: An Agenda. University of Chicago Press. McAfee, A., & Brynjolfsson, E. (2017). Machine, Platform
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Are you an experienced researcher in microbial genomics and bioinformatics with a strong record of university teaching, and expertise in whole-genome sequencing (WGS) analysis, machine learning and