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NAME_FAMILY NAME) : https://nextcloud.univ-lille.fr/index.php/s/ezJxfSBwTjkJCnt Key words: solidification, recycled aluminum alloys, induction heating, thermal simulations, 3D modelling, mechanical testing
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. Viktar Asadchy[AALTO] Co-supervisors/mentors: Dr. Victoria Tormo [INDRA] and Dr. Barthès [3DEUS] Objectives To establish an analytical modeling approach for multilayer tunable metasurfaces that captures
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. 3. Machine Learning and Predictive Analytics: • Develop and apply machine learning models (including Azure Machine Learning) to optimize healthcare data analysis accuracy. • Collaborate with data
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. The project combines interval timing and error monitoring in a novel behavioral task adapted to human and rat models. The leading hypothesis is a read-out model, which assumes that a Timer and a Reader are
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. They will also lead the development of predictive distribution models that incorporate data from the experiment. The project is funded by the USGS CASC. Qualifications Required Qualifications: A completed
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heavily relies on empirical determination of key model parameters. By combining protein structure descriptors, molecular simulations, and machine learning, this PhD project seeks to predict ion-exchange
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regarding the reliability and translational value of in vitro models for predicting carotenoid bioaccessibility across diverse food matrices. The findings will have important implications for nutrition
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Spanish and developing/testing computational models of second-language processing. The work is part of an NSF-funded project Predictive processing in naturalistic language comprehension through EEG and
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application! Your work assignments Spatio-temporal processes are everywhere in science and engineering, with applications ranging from weather prediction to cardiovascular medicine. Developing machine learning
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to capture the spatial complexity of tumor organization and its relationship to treatment response. This PhD project aims to develop robust multimodal predictive models of platinum resistance using a large