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Position Description UNIVERSITY OF SOUTH CAROLINA DEPARTMENT OF MATHEMATICS Postdoctoral Associates in Data Science & Machine Learning The Department of Mathematics at the University of South
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Postdoc (f/m/d) Mechanical Characterization and Materials Assessment for Nuclear Applications / P...
data analysis and statistical methods # Interest in or initial experience with data-driven methods or machine learning is an advantage # Strong communication skills and a collaborative approach to
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methods that combine soundscape targets, acoustic metamaterials, physical modelling, inverse design, machine learning and perceptual evaluation. The postdoc will develop models and design methods
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measurement techniques and PIV. Familiarity with optics, lasers, image processing and statistical data analysis. Familiarity with flow modelling techniques (CFD) or machine learning for fluid flows. Aptitude
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infrastructures. You will contribute to research projects enabling secure, interoperable, and scalable use of clinical data for AI and machine learning applications in complex diseases such as Cancer, Alzheimer's
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University of North Carolina Wilmington | Wilmington, North Carolina | United States | about 12 hours ago
access helps us provide an enriching learning environment for students, faculty and staff interested in the marine sciences. College Center for Marine Science - 306 College College/School Information
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, have experience of working with a variety of machine learning and AI models, be aware of safe and trusted research practice and be comfortable working with experimental datasets. This Vivensa Foundation
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to learn about the rest. The incoming postdoc will work with a lively, energetic group of physicists. The start date is negotiable, preferably late 2026 or early 2027. The application and any questions may
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Area of research: Scientific / postdoctoral posts Job description: Postdoc (f/m/x) in Optoacoustic Tomography 102976 Full time 39 hrs./week Neuherberg near Munich At Helmholtz Munich, we develop
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boson decays, searches for supersymmetry and other new phenomena, and measurements of rare standard model processes. We vigorously pursue the use of machine learning techniques for data analysis