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directions in the group include nanoscale optical probes of magnetic and polar order, plasmon-enhanced light–matter interactions, nonlinear optical imaging of domains, and optical studies of symmetry breaking
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development of the video-based prototype. You will work closely with Model Health and Moveshelf, embedded in the multidisciplinary "Care is coming home!" program, a 5-year consortium of 2 technical universities
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the platform by embedding/developing additional tools for data processing and analysis. The starting point for the developments will be our EasyNMR platform (see easynmr.pastis.dk ). Current application areas
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of materials and devices during switching, combining methods such as laser pump and X ray probe total scattering, WAXS and SAXS, imaging, and femtosecond X ray diffraction to probe structure and dynamics in real
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research. We study the fundamental molecular, cellular, and physiological processes that underly normal and abnormal cardiovascular and metabolic function and we drive the translation of this strong basic
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, with expertise in cell culture (Human ES and/or iPS cells) Web-lab skills, including experience with stem cell culture (human ES and/or iPS cells) and molecular biology Expertise in imaging acquisition
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the PERMANENS Consortium, and will report to the PI, Professor Ella Arensman. The PERMANENS research project aims to develop a prototype of a Clinical Decision Support System (CDSS) software, designed to assist
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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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data without compromising individual privacy. Using unique, nationwide Danish health registry data, you will work with spatial data, such as disease maps and medical imaging. Such data are highly
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, imaging). • Solid foundations in signal processing and statistics. • Experience with machine learning for regression (e.g., tree-based methods, neural networks) • Hands-on experimental skills: ability and