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. Strong programming skills in Python and familiarity with a modern ML stack (e.g., PyTorch, hydra, zarr, dask) Experience in handling and processing large datasets or experience in high-performance
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of interferometric optical systems Perform straylight and ghost analysis to ensure compliance with high-contrast performance requirements Contribute to the development of beam combination and wavefront control
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processing large datasets or experience in high-performance computing (HPC) is an advantage Experience with weather and climate applications and weather ensemble forecasting is an advantage You are creative
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links to the ETH AI Center and the Reliability and Risk Engineering Lab . Job description Collaborate with other researchers to develop high-fidelity emulators for large-scale, energy system optimization
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operating and advancing the data platform, assist interdisciplinary projects that integrate multiple data sources, and use high-performance computing resources to manage and process large environmental
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factors research, the successful candidate will design high-fidelity ICU simulation scenarios, capture a unique synchronized dataset of gaze, speech, and documentation behaviour from practising ICU
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university dedicated to advancing science and technology. Project background We are seeking a highly motivated PhD student to contribute to the further development of SimuCell3D, a high-performance C
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The available position is funded by the Swiss National Science Foundation. This collaborative project (EPF Lausanne, University of Lausanne, ETH Zurich) aims to improve the performance of joint arthroplasty
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diffraction (XRD), scanning electron microscopy (SEM), X-ray computed tomography (XRCT) Expertise in designing and performing high-temperature and high-pressure in-situ experiments is advantageous. Fluency in
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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