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Comprehensive Imaging Education in Biomedical Sciences
Award Imaging Scientist
Funding Cycle Cycle 1
Investigator
Monika Gooz
Medical University of South Carolina
Bio
Monika Gooz is an M.D./Ph.D. scientist with extensive research and higher education experience in biomedical sciences. Her expertise in basic science, particularly in cell signaling, has been applied to different human diseases, including proliferative and fibrotic processes. She also has extensive training in imaging, covering a broad range of modalities (confocal, multiphoton, super-resolution and high content imaging both of live and fixed cells). As manager of the Cell and Molecular Imaging Core and member of the Drug Discovery Core high content imaging team at MUSC, she educates and mentors students and investigators on cutting-edge imaging modalities and image analysis. In addition, she serves as organizer, educator and lecturer in advanced courses on restoration, deconvolution, image analysis, and deep learning. In the last decade, she has been co-organizer and lecturer of the biennial graduate course: Charleston Workshop on Light Microscopy for the Biosciences.
Project Description
To expand the scope and reach of currently available imaging at MUSC, Dr. Gooz aims to develop educational programs to provide a comprehensive theoretical and practical approach to modern imaging. Her goals are: 1) To provide a strong theoretical background to understand image acquisition ending in reproducible and quantifiable sets of data; 2) To demystify artificial intelligence making its application understandable for users; and 3) To teach how to store and handle large datasets. The project will serve the dual purpose of providing comprehensive education in imaging, while at the same time builds reliable databases for further AI-based platform developments. In collaboration with local AI and IT teams, she aims to develop solutions for easily accessible high-content data storage. Dr. Gooz also plans to develop a new graduate course including high content imaging, large data management and advanced image analysis.