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challenging for classical computing architectures. Some of your responsibilities will include: Design and develop mixed-signal circuits for implementing ONNs. Modeling, simulate and benchmark different
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analog circuits for implementing ONNs for computing. Modeling, simulate and benchmark different computing tasks such as sensor data processing. Explore ONN implementation topology and its energy efficiency
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and data-based models for describing complex materials and (re)active molecules with a focus on their interfaces. Development and implementation of new methodologies and algorithms for simulating
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-, ground-, and simulation-based data on the landscape water balance with data analytics to understand how variations in connectivity influence hydrograph characteristics, e.g. flood peaks and drought
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clusters versus sparse stellar associations), assuming a variety of different delivery mechanisms (supernovae, stellar winds). We will use these yields to model the contribution of 26-Al and 60-Fe the long
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experience in manufacturing systems modeling, simulation (i.e., DES), and digital twins. • Good knowledge and experience in machine learning, reinforcement learning, and AI-based optimization for production
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for Extreme Environments The Materials Modeling Group (Prof. Malik Wagih), launching February 2026 in the Department of Materials at ETH Zurich, invites applications for PhD positions starting June 2026 or by
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cases as well as a corpus of existing simulated and real data to be used for validation purposes based on open-data. - Work on a composable architecture able of high-bandwidth I/O, large storage
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. Recent progress in text-to-image generation, fueled by diffusion models and large-scale training, has greatly improved image synthesis aligned with textual prompts. This project, however, focuses on a
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on the project can be found here: https://hecustom.eu/ Total shoulder replacement (TSR) is increasingly offered to younger, more active patients, yet implant loosening and migration remain leading