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Curious about opportunities for learning, creating, discovering, and innovating, and are encouraged to learn from failure. Show Your Fire by joining our team and exhibiting your passion and pride in your
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 2 months ago
-tier machine learning and computer vision venues, actively participating in departmental seminars, and contributing to collaborative projects. Where to apply Website https://jobs.inria.fr/public/classic
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. - Strong expertise in multiscale/multiphysics modeling relevant to catalysis, and experience with machine learning models. - Deep understanding of reaction kinetics, thermodynamics, and structure-reactivity
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. Candidates with background knowledge and hands-on experience in mouse models, proteomics, 3Dorganoids,primary cells purification and culture skills are particularly welcome. Minimum Requirements: Ph.D
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technologies. The candidate will work at the intersection of Artificial Intelligence, Scientific Machine Learning, and Energy Materials, contributing to the design of self-driving laboratories and no-code
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-truth data collection, and operating, testing, validating, and refining crop models to improve prediction accuracy. The candidate will also contribute to the development and application of machine
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 1 month ago
experimental stem cell biology, human and mouse model systems, and machine learning approaches for phenotyping, target discovery, and therapeutic evaluation. Will be hired by the MIT Jameel Clinic for Machine
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to promoting women in Science, Engineering and Technology. Additional Actions : Robotics Nano Technology, Linus, Machine Learning, Large Language Models, AI Safety
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of machine learning methods for archaeological predictive modelling / site discovery Contribute to the design of the archaeological search-process simulator used to train and evaluate AI methods Write grant
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cardiovascular care. Within the consortium, TU Delft contributes expertise in cardiac mechanics, soft tissue modeling, growth and remodeling, machine learning, and uncertainty-aware model personalization. As a