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Posting Description POSTDOCTORAL ASSOCIATE, Mechanical Engineering, to perform cutting-edge research on projects centered around machine learning models for Computer Aided Design and Engineering
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: Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area: Applied Math Position Description: A postdoctoral position is available in the Geometric Machine Learning Group at Harvard
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urban structures * Urban informatics applications for sidewalks analysis ** Candidate Qualifications: * PhD in Physics, Math, Computer Science, Engineering, or a related field. * Strong background in
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, statistics, data science, applied math and/or other quantitative backgrounds who are enthusiastic about bringing their expertise to address fundamental problems in biology and medicine using cutting-edge
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). The position has a 2-1 teaching load and a requirement to be involved with mentoring undergraduate students in research through the Iowa State Math Research Teams (ISMaRT, https://sites.google.com/view/ismart
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for Artificial Intelligence and Natural Sciences at Korea Institute for Advanced Study (KIAS) invites applicants with a Ph.D. in Mathematics, Applied Math, Physics, Chemistry, Neuroscience, Biology, Information
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theory, low-dimensional geometry, functional analysis, combinatorics, and applied math) are valued. Initial appointment is for 24 months, effective July 1, 2026. Decisions concerning a third-year extension
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Duration: 1 year, renewable We are not accepting applications for this job through MathJobs.Org right now. Please apply at https://careers.epfl.ch/job/Lausanne-Postdoctoral-Position-in-Stochastic-Analysis
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that is production-ready for dissemination to other laboratories and for diagnostic use, and the management of large-scale data. They will join a team of computational and experimental postdoctoral fellows
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combinatorics, and flag algebras. The position has a 2-1 teaching load and a requirement to be involved with mentoring undergraduate students in research through the Iowa State Math Research Teams (ISMaRT, https