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data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn't imagine the future, we invent it. If you're passionate about joining a community that challenges the curious to deliver work
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
modeling of large-scale dynamics in networks. This role involves creating large scale models of dynamic phenomena in electrical power networks and quantifying the risk of rare events to mitigate
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challenges in human-health and industry, and iii) generate large-scale enzyme datasets for training next generation protein design models. Jérôme Zürcher – The Zürcher group aims to develop methodology
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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apply quantitative and data-driven models to study protein interactions and their context-dependent behaviour, linking computational predictions with condition-specific biological responses. You will have
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biology, bioinformatics, genomics, statistics, physics, or a related quantitative field Demonstrated ability to analyse large-scale sequencing data using R, Python or equivalent A self-motivated team player
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multimodal vision-language models for prompt-based 3D medical image segmentation Work with large-scale clinical CT datasets and scalable deep learning pipelines Validate models in close collaboration with
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. It is situated in the Big Data Institute on the University’s Old Road Campus, giving it ready access to major medical research institutes such as the Clinical Trials Service Unit, the Oxford Centre
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Requisition Details GENERAL REQUISITION INFORMATION EEO Statement: Location Omaha, NE Requisition Number: 2026 - 052 Department Genetics Cell Biology & Anatomy 50000507 Business Unit(College
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Range $62,232/yr Type of Position Staff Position Time Status Full-Time Required Education PhD/ ScD, DrPH Required Related Experience Population health/ public health, specifically using quantitative