We are inviting applications for a full-time postdoctoral scholar with a strong computational background and interest in leading the development of clinical deep learning and other machine learning models to enable improved diagnosis, prognostication, and prediction of treatment response for bladder cancer, specifically related to endoscopic imaging and surgery. The postdoctoral scholar will be co-mentored by Professor Joseph Liao in the Department of Urology and Professor Lei Xing in the Department of Radiation Oncology. Creative, highly motivated individuals with strong problem-solving skills, a record of scholarly productivity, and the ability to work independently, yet collaboratively, in a multidisciplinary environment with clinicians, computer scientists, and statisticians, are strongly encouraged to apply. Previous experience working with optical imaging and computer vision is a strong plus.
The successful candidate will be jointly based in the Department of Urology at the Stanford University School of Medicine and will be affiliated with Department of Radiation Oncology and the Center for Artificial Intelligence in Medicine & Imaging (AIMI), with opportunities to work with a diverse and dynamic group of researchers applying AI to solve clinically important problems in healthcare.
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