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Field
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the intersection of machine learning (ML) and the sounds of wildlife (“bioacoustics”). We are also happy to consider candidates in one of the two fields who can demonstrate a strong basis for working in this cross
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practical knowledge of statistical and programming packages is mandatory, including R, Python, and/or SQL. Extensive experience with advanced statistical techniques and algorithms, such as Machine Learning
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Department with significant expertise in Machine Learning/AI are available to help provide overall guidance and strategy to the postdoc. Stanford Departments and Centers: Anesthesiology, Perioperative and Pain
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the application of statistics and machine learning in social science. The position requires no teaching, though teaching opportunities may be provided if requested. When teaching, successful candidates will carry
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Requisition Id 16802 Overview: We are seeking a Postdoctoral Research Associate for the development and application of advanced multiphysics simulations, and machine learning (ML) methods relevant
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Researcher in The School of Chemistry. The InTeleCat project involves the use of machine learning and AI as applied to organic synthesis. It is a large collaborative project involving researchers in the US
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(postdoc) Limited until: 14.10.2032 Reference no.: 5906 Explore and teach at the University of Vienna, where over 7,500 brilliant minds have found a unique balance of freedom and support. Join us if you’re
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. Possible research topics include: Scientific machine learning Numerical partial differential equations (PDEs) Computational fluid dynamics Neural operators High-performance computing Data-driven
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to present their work and learn from others. Fellows are also encouraged to engage with colleagues and attend departmental seminars. Applicants must demonstrate outstanding scholarly achievement and promise
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energised — not deterred — by problems that sit between physics, learning and the messy real world. Your experience and profile: a PhD (completed or near completion) in Machine Learning, Computer Vision