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for extracting physiological biomarkers from ECG, PPG, and related sensor data Machine learning and AI for predictive modelling and risk stratification Computational physiology modelling to personalise and
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passionate about sustainability, clean energy, and water treatment technologies?Are you skilled in machine learning, process modelling, or chemical engineering simulations?Are you excited by the idea
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(supervisor) The position holder will be required to perform the following tasks/will do research on the following topics: Software engineering practices for machine learning Tabular machine learning Large
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the use of hierarchical graph neural networks for modeling multi-scale urban energy systems. By combining advances in Physics-Informed Machine Learning (PIML) and Graph Neural Networks (GNNs) with real
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, engineering, physical sciences, economics or any other field where evidence is provided of sufficient computing and mathematical background) solid experience of programming, machine learning methods and ideally
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap
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processes that produce energy and raw materials. The Department of Thermodynamics of Actinides is looking for a PhD Student (f/m/d) - Machine Learning for Modelling Complex Geochemical Systems. The job
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requirements: a master's degree in electrical engineering (preferably with a focus on electrical machines or electrical drives) a clear interest in the topic of the position excellent command of English strong
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17 Oct 2025 Job Information Organisation/Company ETH Zürich Research Field Chemistry » Other Engineering » Chemical engineering Engineering » Computer engineering Engineering » Electrical
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and implementing innovative solutions at the intersection of sensor data collection, machine learning, and real-time decision-making. Specifically, the candidate will contribute to projects focused