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range of topics related to imaging with geophysical data. Our research focuses on mathematical methods for processing, imaging, and inversion of geophysical data, the physics of wave propagation, and the
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for anomaly detection Design multimodal learning approaches that fuse image data with time-series sensor data for monitoring powder bed fusion processes Develop and maintain research codebases for training
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G. M. Silva, within the group of Prof. Roman Stocker, and focuses on the development and deployment of a new‑generation underwater imaging device to transform drift studies in riverine ecosystems. It
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, production-quality systems. We are seeking an expert in 3D garment reconstruction from multi-view images to join our team at the ETH AI Center. Project background We are looking to fill this role as part of
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energy transfer, developing and employing computer simulations, laboratory experiments, and field analyses. Our aim is to gain fundamental insights and develop sustainable technologies to address societal
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motivated individual to develop Python tools for analyzing data from our holographic cloud particle imagers. Our research group studies the crucial role of clouds and aerosols in the climate system, aiming
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of mathematics, computer science, and evolutionary biology. We develop methods to understand evolutionary, ecological, epidemiological, and developmental processes on different scales based on genetic data. In our
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80%, Zurich, fixed-term The Laboratory of Molecular Medicine, led by Prof. Yohei Yamauchi, is developing the ViViD-AFM V2.0—a next-generation nano-imaging system. This project focuses
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100%, Basel, fixed-term The Computational Biology (CoBi) group, led by Prof. Dagmar Iber, develops data-driven, mechanistic models of biological systems using advanced imaging and computational
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operations that are yet to be fully understood. In this context, it is evident that the operation, control, and planning of power systems will soon be pushed to their limits. Therefore, new computational