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, cardiovascular diseases and rare diseases. This specific role focuses on engineering CAR-T cells and developing programmable gene control systems to improve safety and therapeutic efficacy. The successful
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psychoactive substances, in seized drug products or clinical samples. The candidate will have the opportunity to work directly with experimentalists to validate predictions made by their machine-learning models
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on advanced machine learning and emulation approaches. Key responsibilities: The candidates will be expected to work on the following tasks: - Develop machine learning (ML) methodologies appropriate
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related to staff position within a Research Infrastructure? No Offer Description ELLIS Institute Finland is a newly established world-class research hub in AI and machine learning – and we are growing! We
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responsibility of developing predictive tools based on machine learning for the analysis and interpretation of Raman vibrational spectra applied to battery materials. The successful candidate will design and
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Project Overview We are hiring highly motivated and talented Postdoctoral Associates who are interested in advancing the state of the art in resource-efficient machine learning at the Singapore-MIT
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knowledge and advanced transfer learning techniques. The methodology incorporates fundamental radar wave propagation equations into the diffusion process, allowing for more accurate and physically consistent
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Experience in machine learning, math, and programming. LanguagesENGLISHLevelGood Additional Information Work Location(s) Number of offers available1Company/InstituteUniverCountryBrazilState
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computational mechanics and scientific machine learning. The successful candidate will work on the design of hybrid, physics-informed modeling and identification frameworks for complex dissipative material
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development, and publication in peer-reviewed venues. Strong background in machine learning, with research experience in deep learning, foundation models, or related areas. Solid programming ability in Python