376 computer-science-intern-"https:"-"https:"-"https:"-"https:"-"U.S"-"UCL" positions in Switzerland
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scientometrics Profile Background Master’s degree ideally in information science, library science, data science, computer science, or a comparable field; a PhD is an advantage Regardless of academic background
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dynamical systems, and machine learning, with applications to synthetic biology and biomolecular circuit design. Our research develops mathematical and computational frameworks for understanding and
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interest and motivation to contribute to the project’s goals (see Job description section above) Outstanding academic record, including an excellent Master’s degree in Computer Science, Engineering, or other
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Science at the ETH Zurich Institute of Environmental Engineering, with expertise in water chemistry assessments in forested ecosystems. The Silviculture group is part of the Chair of Forest Resources
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datasets The position is limited to two years. Profile University degree (MSc or PhD) in data science, computer science, physics or a related field Experience in training and validating large-scale deep
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Laboratories for Materials Science and Technology (Empa). Our team is highly interdisciplinary and international, providing an inspiring environment for high impact research. We have internal expertise in (micro
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evaluate prototypes together with industrial partners Profile Required experience CH/EU/EFTA citizenship or valid Swiss work permit PhD in Engineering, Computer Science, Robotics, or related field Strong
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Materials science and technology are our passion. With our cutting-edge research, Empa's around 1,100 employees make essential contributions to the well-being of society for a future worth living
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years. Profile University degree (MSc or PhD) in data science, computer science, physics or a related field Experience in training and validating large-scale deep-learning models on distributed systems
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will be put in place. Profile The ideal candidate will hold a PhD or equivalent in bioinformatics, computational biology, computer science, applied statistics, or a related field, with substantial (>6