Position overview Salary range: The salary range for this position is $66,737-$80,034. The posted UC salary scales set the minimum pay determined by experience level. See: Postdoc Scholar Salary Scale Effective 10/1/26: The salary range for this position is $71,491-$85,736. See: Postdoc Scholar Salary Scale Application Window Open date: July 1, 2026 Next review date: Tuesday, Sep 1, 2026 at 11:59pm (Pacific Time)
Apply by this date to ensure full consideration by the committee. Final date: Wednesday, Jun 30, 2027 at 11:59pm (Pacific Time) Applications will continue to be accepted until this date, but those received after the review date will only be considered if the position has not yet been filled. Position description The Computational Medicine Research Group led by Prof. Pratik Shah at the University of California,
Irvine, invites applications for a Postdoctoral Scholar position. The lab seeks outstanding PhD or MD, PhD applicants with strong academic backgrounds in computer science, biomedical informatics, biomedical engineering, statistics, or related fields. The lab is engaged in developing novel deep learning and AI-based technologies for digital biopsies from medical images and real-world clinical decision-making from
non-imaging datasets, with research published in top journals such as Cell Reports Methods, Nature Digital Medicine, JAMA, IEEE Conferences, and Proceedings of National Academies of Science Engineering and Medicine Workshops. Selected candidates will have the opportunity to train for publishing in leading biomedical journals and machine learning conferences, networking with government funding agencies, industry
partners, foundations, and academic experts. Training in fellowship writing, teaching/mentoring, oral presentations and review of manuscripts will be provided. For more information about the research group, publications, projects, and Prof. Shah, please visit: Shah Lab; About Prof. Shah The candidate will contribute to two key research areas: Generative AI for Medical Imaging and Digital Biopsies Develop and
interpret deep neural networks (DNNs) for automating non-destructive tissue-based analyses using high-parameter medical images (e.g., pathology, MRI, CT, and RGB) and molecular profiles. Conduct hypothesis-driven research to link molecular profiles to disease biology. Focus on generating and validating diagnostic tools for clinical use. Generative and Predictive AI for Clinical Decision Support and Statistical
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