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knowledge in parallel/GPU computing. Job Duties Job Duty Doing research problems in the area of mathematical foundations of data science and machine learning. The postdoc will assist with ongoing research
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Posted on Tue, 04/07/2026 - 20:37 Important Info Faculty Sponsor First name: Stephen Faculty Sponsor Last Name: Hinshaw Stanford Departments and Centers: Molecular and Cellular Physiology Postdoc
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communication in parallel/distributed AI/ML Enhancement of AI/ML with in-network computing & processing Adaptation & optimization of AI/ML software libraries for non-conventional hardware architectures Physics
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applications with related expertise. Experience with sequencing approaches to study RNA turnover or with massively parallel reporter assays(MPRAs) will be beneficial. Must Have Bioinformatics experience in
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, including parallel computing frameworks, C/C++, Julia and/or python Experience with training AI surrogate and/or inverse models Experience working in underground laboratories and/or clean rooms Excellent
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of human biological fluids (such as blood and urine), to ensure successful implementation in various clinical and exposomics applications. In parallel, methods for targeted metabolomics/lipidomics need to be
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» Nuclear engineering Engineering » Control engineering Engineering » Mechanical engineering Physics » Electronics Researcher Profile Recognised Researcher (R2) Positions Postdoc Positions Application
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develop computational fluid dynamic (CFD) tools that make exascale computing accessible to a broader set of users. The successful candidate will develop a massively parallel solver, capable of running
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supervision of Prof. Yingda Cheng on computational methods and modeling for kinetic equations. The research conducted will involve development of numerical methods, development and analysis of reduced order