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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
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component of solid-state transformers (SSTs). Such SSTs are required, for example, in future AI data centres, where power consumption per computer rack increases to levels of several hundred kilowatts or even
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dynamical systems, and machine learning, with applications to synthetic biology and biomolecular circuit design. Our research develops mathematical and computational frameworks for understanding and
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Transcriptomics Specialist; Image Analysis Specialist (this position); Computational Neuroscience and Data Analysis Specialist. These positions will work closely together and will support a broad user base across
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Transcriptomics Specialist (this position); Image Analysis Specialist; Computational Neuroscience and Data Analysis Specialist. These positions will work closely together and will support a broad user base across
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datasets The position is limited to two years. Profile University degree (MSc or PhD) in data science, computer science, physics or a related field Experience in training and validating large-scale deep
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years. Profile University degree (MSc or PhD) in data science, computer science, physics or a related field Experience in training and validating large-scale deep-learning models on distributed systems
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convective heat transfer with the surrounding air. Within our research group at ETH Zurich, we are developing computational workflows for predicting temperature fields in machine tools using computational
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scientometrics Profile Background Master’s degree ideally in information science, library science, data science, computer science, or a comparable field; a PhD is an advantage Regardless of academic background
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Joint Research Centre under the Collaborative Doctoral Partnerships programme. For further information and detailed task description please see link below. Your profile Qualifications and Specific