208 computer-science-intern-"https:"-"https:"-"https:"-"https:"-"U.S" positions at ETH Zurich
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, Switzerland [map ] Subject Areas: Computer Science / Distributed Systems and Networking , Networking , Networking and distributed systems Appl Deadline: 2026/01/08 11:59PM (posted 2025/11/10, listed until
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, neuroscientists, computer scientists, clinicians, and data scientists across the Singapore-ETH Centre (SEC), the National University of Singapore (NUS), and Nanyang Technological University (NTU), the PhD student
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or mechanical engineering, or CS Solid knowledge of computer vision and ML, particularly anomaly detection methods Experience with multimodal data (e.g., image + time series, sensor fusion) is a strong ad-vantage
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convective heat transfer with the surrounding air. Within our research group at ETH Zurich, we are developing computational workflows for predicting temperature fields in machine tools using computational
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data Coordinate with researchers in climate science, environmental monitoring, data science, and related fields Collaborate with a dynamic and international team of developers and researchers developers
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(Bayesian) phylodynamics. A Master degree in computer science, bioinformatics, or a related field. Interest in working with an interdisciplinary and international team. We value an open and inclusive group
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Computer Science, Biomedical Engineering, Data Science, Cognitive Science, or a related field Strong Python programming skills and experience with PyTorch or TensorFlow Interest in multimodal data, time-series
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implementation strategy to drive the LIFE Space Mission to successful launch and operations. To support the mission concept study, we opened two positions in Optical Engineering. Project background LIFE brings
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of Medical Microbiology at the University of Zurich, the Department of Informatics at ETHZ and several further partners, we address the challenge by the combining microfluidic technology, sequencing and fast
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at the University of Zurich, the Department of Informatics at ETHZ and several further partners, we address the challenge by the combining microfluidic technology, sequencing and fast data analysis. In