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, computational quantum many-body physics, and machine learning The Quantum AI lab at ETH (Prof. Juan Carrasquilla ) invites applications for postdoctoral positions to work at the intersection of computational
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in computational science, machine learning, and experience with synchrotron data analysis are strongly encouraged to apply. Position Requirements PhD completed in the past 5 years or soon to be
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, atmospheric signals), data fusion across sensing modalities, and development of scalable machine learning pipelines. Work will be entirely computational and based in Seattle, with no field deployment
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The postdoctoral researcher will work with computer-based analytical methods and large databases to develop theory and methodology for utilising aggregated data from archaeology, genetics, and linguistics, thereby
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environment for all employees through mutual respect and tolerance. Description of the project The postdoc will leverage existing high-throughput data from large scale cohorts and large family cohorts
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(CAVs) Traffic control and signal optimisation Navigation and routing strategies Operations research and network optimisation Big data analytics and machine learning Mōu | Who You Are To be successful in
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, data normalisation and machine learning methods applied to biological datasets Experience with data management and version control (Git/GitHub, workflow automation, documentation) Capacity to work
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learning, transfer learning, foundation models, and self-supervised learning. Experience in dealing with large medical datasets (e.g., electronic health records data or medical images) Ability to use high
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website incorporating this data. Extensive computer coding experience. Extensive independent teaching experience and excellent communication skills. Excellent interpersonal skills and the ability to work
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skills. Aware of the ethical issues around working with Big Data. Desirable criteria Experience applying advanced statistical or machine learning methods to complex datasets. Evidence of involvement in