Research Intern - Diagnostic Imaging AI, Imaging Computing, Reconstruction and Inverse Problem

Research Interns put inquiry and theory into practice. Alongside fellow doctoral candidates and some of the world's best researchers, Research Interns learn, collaborate, and network for life. Research Interns not only advance their own careers, but they also contribute to exciting research and development strides. During the 12-week internship, Research Interns are paired with mentors and expected to collaborate with other Research Interns and researchers, present findings, and contribute to the vibrant life of the community. Research internships are available in all areas of research, and are offered year-round, though they typically begin in the summer. Research Interns will conduct research in following domains: New imaging model architecture and training methods. Image reconstruction algorithms to solve inverse problems and implementation. Model evaluation, uncertainty, imaging artifacts, and hallucination analysis. Imaging application development and deployment. Currently enrolled in a PhD program in a related STEM field. At least 2 years of research experiences with deep learning for imaging. At least one publication at peer-reviewed journals or international conferences in imaging and AI fields. In addition to the qualifications below, you'll need to submit a minimum of two reference letters for this position as well as a cover letter and any relevant work or research samples. After you submit your application, a request for letters may be sent to your list of references on your behalf. Note that reference letters cannot be requested until after you have submitted your application, and furthermore, that they might not be automatically requested for all candidates. You may wish to alert your letter writers in advance, so they will be ready to submit your letter. Familiar with Pytorch and model training. Understanding multi-GPU training.

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