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. The focus of this position is developing methods to disentangle dynamic, multiscale ecological signals from large, noisy observational data. This work lies at the interface of statistics, machine learning/AI
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goals and those of faculty mentor; and publication of research findings/scholarship during postdoc appointment period. Projects in the Rocha lab address the evolutionary history of populations and species
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models that provide evidence-based reasoning for mission-critical decisions. Explainable AI for mission-critical decision support: design interpretable machine learning architectures capable of offering
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, generous retirement benefits, and a wide array of family-friendly and cultural programs to eligible team members. Learn more at https://hr.duke.edu/benefits/ Duke is an Equal Opportunity Employer committed
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postdoc with interests in RNA virology and host-pathogen interactions. For detailed information about the laboratory’s research, see our website (http://www.mouncelab.com). Experience in molecular virology
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machine learning are encouraged to apply. The postdoc will also play a leading role in co-mentoring graduate and undergraduate students, assist in organizing seminars and activities related to RTG
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Processing and Image Analysis Group, Section for Machine Learning, Department of Informatics. You will be part of Visual Intelligence and the DSB group. For more information about the position see https
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Postdoc Positions Application Deadline 25 Mar 2026 - 23:59 (Europe/Copenhagen) Country Denmark Type of Contract Temporary Job Status Full-time Hours Per Week 37 Offer Starting Date 1 Jun 2026 Is the job
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an integrated framework to explore advanced workloads including simulations with in-situ visualization and, possibly, machine learning integration. This work will inform future ALCF platform procurement decisions
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) | Working hours: 20,00 | Classification CBA: §48 VwGr. B1 lit. b (postdoc) Limited contract until: 31.03.2032 Job ID: 5115 Explore and teach at the University of Vienna, where over 7,500 brilliant minds