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includes the design and manufacturing of miniaturized platforms and their optimization for biochemical assays and analytical procedures. For a third-party funded project, running for four years, we
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includes the design and manufacturing of miniaturized platforms and their optimization for biochemical assays and analytical procedures. For a third-party funded project, running for four years, we
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, optimized for high-performance computing (HPC) environments Classifying ice crystal habits using Convolutional Neural Networks (CNNs) Providing intuitive graphical interfaces for user interaction and data
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and adaptability, be able to work under time pressure Have good knowledge of German and English (oral/written) Workplace Workplace We offer The University and ETH Zürich offer optimal working conditions
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) distributional generalization, transfer learning, causality Multi-objective settings and alignment, RL theory Statistical learning theory, optimization (e.g., implicit bias) Robustness (broadly defined), privacy
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densification, (iv) changes in glacier surface albedo. Particular objectives include the development of frameworks to infer optimal physical parameters and downscaling of meteorology through assimilation
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for a duration of 4 years. The optimal starting date for this position is September 2026.
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interest in optimization What we value Research mindset and intellectual curiosity Ability to work independently Clear communication of ideas and results Workplace Workplace We offer Your job with impact
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the realization of 1:1 full-scale prototypes Assist in robotic fabrication and digital production workflows Contribute to material testing, system optimization, and physical prototyping Support
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-cell data) using existing pipelines Demonstrated ability to enhance, optimize, and extend existing computational pipelines, as well as design and implement new workflows Experience working with large and