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MD degree. Must have relevant background in Biological/Biomedical Sciences or related Engineering field with a specific focus in cardiology, cardiovascular diseases, and cardiac imaging. Must have
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motivated candidate, who will develop and support projects at the intersection of soft matter physics and food science. The Postdoc position is part of the Food technology group at the Department of Food
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(10kHz) as well as standard PIV, LDV, PDA, Raman, Rayleigh and LIF. Computational capabilities include Large Eddy Simulations (LES), Probability Density Function (PDF) and Multiple Mapping Conditioning
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clinically managed only in its advanced stage that is marked by excessive multiplication and leakiness of blood vessels in the inner retina. However, there is growing recognition that more effective treatment
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motivated candidate, who will develop and support projects at the intersection of soft matter physics and food science. The Postdoc position is part of the Food technology group at the Department of Food
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interdisciplinary research by bringing together its core faculty in computer science, statistics, and engineering with scholars from management, law, and social sciences. Together, they work to understand, model, and
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informatics, electrical engineering, or a related field Demonstrated expertise in machine learning, deep learning, and image-based modeling. A strong publication record in top-tier venues (e.g., MICCAI, CVPR
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multiple sclerosis (MS) and Alzheimer’s Disease (AD). These lipid-loaded microglia are associated with disease pathology and enhance neuroinflammation, myelin breakdown, and neuronal loss. Although brain
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measure success. Basic Qualifications: A PhD in Materials Science and Engineering or a related field completed within the last 5 years Preferred Qualifications: Strong background in computational and image
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Experimental Solid Mechanics Laboratory. This position offers a unique opportunity to conduct cutting-edge research at the intersection of materials science, mechanical engineering, and applied physics