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and infrared observations to improve the precision of transit parameters and to disentangle stellar and atmospheric variability from planetary signals. This will involve developing advanced techniques
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flow reconstruction, enabling both real-time coarse diagnostics and high-fidelity offline velocity field estimation. Developing reinforcement learning (RL) algorithms for a multi-agent robotics system
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A doctoral student is sought from spring 2026 for a research project at the Institute of Environmental Engineering (IFU), Chair Earth Observation at the ETH Zürich on Snow and ice parameter
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-parameter flow-cytometry, as well as murine models and human organoid technology to investigate mechanisms of longevity of immunological T and B cell memory. A strong interest in quantitative disciplines
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23 Jan 2026 Job Information Organisation/Company ETH Zürich Research Field Computer science » Computer architecture Computer science » Programming Computer science » Other Engineering » Biomedical
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, advanced high-parameter flow-cytometry, as well as murine models and human organoid technology to investigate mechanisms of longevity of immunological T and B cell memory. A strong interest in quantitative
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Computational Design Lab and work at the interface of computer vision, computer graphics, hardware, and extended reality. The project is part of ETHAR, a new research initiative at ETH Zürich with a unique focus
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AI and signal preprocessing: Implement on-node feature extraction (FFT, modal parameters, transmissibility metrics) and deploy quantized TinyML models co-developed with ADC1. Enable adaptive sensing