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Your profile PhD applicants must possess a Master's degree in mathematics, theoretical physics, or computer science. Candidates should have an exceptional academic record and a robust mathematical foundation. While research experience is advantageous for PhD applicants, it is not...
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Your position Our group conducts research at the intersection of artificial intelligence (AI) and pediatric healthcare, developing AI and machine learning (ML) methods to address real-world clinical
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willingness to learn A solid foundation in experimental research, data analysis, and scientific methods Interest in machine learning and data-driven approaches to materials discovery Strong interest in hands
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velocity changes at selected locations with the introduction of unsupervised machine learning and study the interaction of mass balance changes (crustal stress changes) and geohazards such as rain-induced
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will work within the Computational Mechanics Group of ETH Zürich in collaboration with industrial partners. You will have the unique opportunity to learn, develop and apply a range of cutting-edge
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strong willingness to learn A solid foundation in experimental research, data analysis, and scientific methods Interest in machine learning and data-driven approaches to materials discovery Strong interest
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or similar tools) Initial experience with machine learning, clustering methods or generative AI (preferred but not required) Willingness and ability to collaborate with researchers from different backgrounds
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. Above all, we are seeking highly motivated and enthusiastic scientists who thrive in collaborative working environments, enjoy taking on challenges, learning new skills, critical thinking and problem
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university . You can expect numerous benefits , such as public transport season tickets and car sharing, a wide range of sports offered by the ASVZ, childcare and attractive pension benefits. chevron_right