Postdoctoral Fellow at National Institutes of Health
Bethesda, Maryland, United States
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Summary
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Brad Busse is a Postdoctoral Fellow with 13 years of experience applying advanced data science and image-processing techniques to biomedical research, blending deep learning, classical computer vision and statistical analysis. He is fluent in Python and familiar with Matlab, Java and C++, and has built practical pipelines from active learning classifiers for high-dimensional imaging to level-set segmentation for protein quantification. At the NIH he developed tissue-preservation methods for iterative immunofluorescence, led mentorship initiatives, and delivered a deep learning system to detect muscle damage—work that bridges algorithm development and hands-on microscopy. Comfortable leading diverse teams, he has a track record of turning messy experimental imaging data into reproducible, statistically meaningful results and mentoring others to do the same. An unusual strength is his combination of microscope planning and SIFT-based motion analysis expertise, enabling quantitative study of cellular migration in challenging biological systems.
13 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy - PhD, Biophysics, Doctor of Philosophy - PhD, Biophysics at Stanford University
Contributions:74 pushes, 2 branches in 2 years 1 month
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Brad Busse - Postdoctoral Fellow at National Institutes of Health