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image analysis packages such as Freesurfer, FSL, SPM, or 3DSlicer, or using machine learning or artificial intelligence models would be advantageous What We Offer The appointee would be exposed to ample
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applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine learning applications in process industries; advanced process control (APC); model predictive control (MPC); digital
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to the development, adaptation, and application of machine‑learning models tailored to RODI data (in collaboration with project partners). Designing and implementing an innovative image‑based database to manage and
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radiation beamline hands-on experience in X?ray microscopy techniques, X?ray diffraction or X?ray fluorescence working knowledge of image processing e.g. using machine learning German skills For further
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of Researchers and the Open, Transparent and Merit-Based Recruitment of Researchers (OTM-R) Policy at the Wrocław University of Science and Technology. LINK PL: https://pwr.edu.pl/uczelnia/europejska-strategia-dla
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communication skills. • Track record of conducting original research and publishing in peer-reviewed scientific journals. Preferred Qualifications • Experience in remote sensing or machine learning applications
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competitive ERC. The project focuses on the development of a first-principles, machine-learning-accelerated computational framework for modelling polymorphism, anharmonicity, and electron–phonon interactions in
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
Engineering stresses the application of science and engineering, mathematical analysis, and computer techniques to biomedical problems. The research and entrepreneurship of the faculty, students, and staff aim
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of strains) to in-field testing of up to 800 strains. The scale and standardized approach will create a unique foundation for advanced data analysis, including AI, machine learning, and statistical modelling
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analysis and biomedical data analysis, with demonstrated experience in organ segmentation from medical images, using both traditional and machine learning–based methods, and creation of large segmentation