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novel biosensors, gene switches, genetic closed-loop circuits, and chemical structures that interface with and actuate cellular activities, we design programmable cellular implants and devices
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platforms such as novel biosensors, gene switches, genetic closed-loop circuits, and chemical structures that interface with and actuate cellular activities, we design programmable cellular implants and
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-dimensional biological datasets, developing and maintaining bioinformatics pipelines, and collaborating closely with experimental scientists to translate computational findings into biological insight
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using emerging non-invasive exhalomics (exhaled breath metabolomics) approach. The research program integrates animal experiments with advanced analytical techniques and bioinformatics to enhance
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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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policy, political economy, economics, sociology, computational social sciences, or a related field Strong knowledge of advanced quantitative methods is essential (e.g., econometrics, causal inference
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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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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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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