62 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "University of Waterloo" uni jobs at Chalmers University of Technology in Sweden
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contribute to exciting research in theory of machine learning, in a collaborative and dynamic environment. In the rapidly growing area of artificial intelligence (AI), this position is a uniqure chance to
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combining two of Europe's new satellite sensors. If you have interests in physics, climate and machine learning, this is the Doctoral student position for you! About us Our team is part of the Division
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at the Division of Data Science and AI at the Department of Computer Science and Engineering . Join our innovative team and contribute to exciting research in theory of machine learning, in a collaborative and
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. The main research problems include mathematical theory, algorithms, and machine learning (deep learning) for inverse problems in artificial intelligence, as well as application to medical problems. About the
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60 credits* in Computer Science, Electrical engineering, or equivalent. You will need strong written and verbal communication skills in English. Strong machine learning fundamentals (probability
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, Computer Science, Bioinformatics, Machine Learning or related fields. You need excellent programming skills and an ability to design and implement machine learning-based projects. You need a strong
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of biomathematics, biostatistics, spatial modeling, differential equations, Bayesian inference, large-scale computational methods, bioinformatics, data science, machine learning, optimisation, numerical methods
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significant modeling challenge. This project addresses that challenge by combining machine learning with constitutive modeling, while ensuring adherence to physical laws. Although the primary focus is on large
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complex behavior under demanding operating conditions presents a significant modeling challenge. This project addresses that challenge by combining machine learning with constitutive modeling, while
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, or quantum-inspired methods Experience with hybrid quantum–classical algorithms or optimization methods Background in uncertainty quantification, reduced-order modeling, or machine learning Experience