167 assistant-professor-computer-"https:"-"https:"-"https:"-"https:" positions at ETH Zurich in Switzerland
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metadata and access standards to support data discovery and reproducibility. Working closely with researchers and developers from C2SM, ETH, and CSCS, the successful candidate will help operate and advance
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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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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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preparation workflows and QA/QC concepts. Provide consultation during experimental design (e.g., selection of analytical approach, measurement strategy, controls, and interpretation limits) and help translate
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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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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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. Our well-equipped Makerspace provides access to a wide range of tools and equipment for prototyping. To help projects grow beyond the idea stage, we also offer co-working, ideation, and event spaces, as
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. Our well-equipped Makerspace provides access to a wide range of tools and equipment for prototyping. To help projects grow beyond the idea stage, we also offer co-working, ideation, and event spaces, as
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), lower back pain, neuro-degenerative disorders and neurological tumors. At the core of our research is the collaboration across disciplines spanning expertise in medicine, biology, computer and data