The successful candidate will develop statistical models for functional MRI data acquired in the context of non-invasive neuromodulation.
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The successful candidate will support NIH-funded collaboration between the CNS Imaging Group and several other departments at the University.
The successful candidates will design, implement and test software for advanced computer vision or machine learning tasks.
The successful candidates will contribute to the development of a platform that enables ultra-fast mapping of indoor environments.
The research will focus on developing quantitative breast imaging analysis methods, and applying them to process large-scale real clinical image data for clinical research studies.
The research will focus on SLAM and development of realtime algorithms on mobile platforms.
The successful candidates will research, design, and implement algorithms for medical image understanding.