Stanford’s AIMI Center is hiring talented individuals who bring new perspectives and skills to our multi-disciplinary team. If you are looking for collaborative clinicians and engineers across multiple Stanford schools, and exciting projects with high clinical relevance, then you are in the right place.
The new Center for Artificial Intelligence in Medicine and Imaging (AIMI Center) at Stanford University is seeking a post-doctoral scholar to develop new machine learning methods for oncologic imaging. The candidate will lead a research program developing machine learning methods and other tools to detect and characterize cancer on radiologic images, using not only imaging information. The post-doctoral scholar will work with AIMI Center faculty under the general direction of the AIMI Center Director and Associate Director, developing projects related to the radiologic imaging of cancer. We have a special interest in breast cancer but will consider applicants with interest in imaging any cancer.
The mission of the AIMI Center (http://aimi.stanford.edu) is to develop and evaluate machine learning methods for medical images to improve the health of patients. The center is a collaboration between the Schools of Medicine and Engineering at Stanford, engaging more than 40 affiliated faculty from 8 academic departments. Our research projects are collaborations between clinical and technical experts, employing massive curated medical imaging data sets to produce systems that improve healthcare. The methods we develop accelerate early disease detection, improve treatment selection, and reduce diagnostic imaging errors. The AIMI Center is a unique place to expose state-of-the-art machine learning algorithms to the medical imaging practice environment and help transform medical practice. We work closely with partners across the Stanford campus as well as large technology companies and startups to manage practical clinical problems and bring our advances directly to patients.
Candidates should have a doctoral degree in computer science or a related data science discipline and a publication record or equivalent experience in machine learning and computer vision. The candidate must have desire to seek translational collaborations with investigators pursuing similar research goals inside and outside of Stanford. We seek motivated individuals who are committed not only to excellence in research, but also to training the next generation of researchers. Medical training or experience is desirable but not required. This fellowship is supported by the Paustenbach Medical AI Research Fund. Appointment is for two years, with an option to extend for an additional year. Stanford University limits post-doctoral appointments to three years. To apply, please send your CV and a cover letter to firstname.lastname@example.org .
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