Role OverviewThe Postdoctoral Research Scholar will work on developing and applying computational methods for the analysis of high-speed laryngeal videoendoscopy recordings, contributing to NIH-funded research on vocal fold physiology and laryngeal imaging. The scholar will join a collaborative and interdisciplinary research environment with opportunities to develop novel computational methods, publish in leading journals, mentor student researchers, and contribute to ongoing NIH-funded projects.
What You Will Do
Develop and evaluate computer vision, machine learning, and deep learning approaches for the analysis of laryngeal images and related biomedical data, analyze and integrate multimodal datasets, prepare manuscripts for publication, and mentor graduate and undergraduate researchers.
Why It Might Be a Fit
The successful candidate will have a strong engineering and computational background, experience with deep learning, and proficiency in Python and/or MATLAB. The scholar will contribute to a highly interdisciplinary research environment at the intersection of engineering, artificial intelligence, and clinical science.
Requirements
- PhD in Biomedical Engineering, Electrical Engineering, Computer Science, or a related field
- Proficiency in Python and/or MATLAB
- Experience with deep learning, including PyTorch and/or TensorFlow
- Experience developing, training, and evaluating computer vision and image segmentation models
- Strong foundations in image processing and machine learning
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