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<div class="isg-job-description“>position overview
Open date: July 9, 2025
Next review date: Saturday, Aug 9, 2025 at 11:59pm (Pacific Time)
Apply by this date to ensure full consideration by the committee.
Final date: Tuesday, Jun 30, 2026 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 Postdoctoral Scholar position. The lab seeks outstanding Ph.D. or M.D., Ph.D. 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: https://faculty.sites.uci.edu/pratikshahlab/; https://www.pratiks.info/
The candidate will contribute to two key research areas:
Responsibilities:
* Collecting, preprocessing, and visualizing high-dimensional medical images, non-imaging clinical (EMR), and genetic sequencing datasets
* Training and validating generative deep learning (e.g., GANs, Diffusion, Transformers) and deep reinforcement learning models
* Developing novel statistical models for uncertainty quantification, causality estimation, and prediction accuracy
* Publishing research in leading biomedical and machine learning journals and conferences
* Engaging with industry partners, government agencies, and academic experts
* Strong analytical, organizational, and communication skills
* Committed to mentoring and teaching
Department: https://medschool.uci.edu/research/clinical-departments/pathology-laboratory-medicine
Qualifications
PhD. or MD, PhD. in computer science, biomedical informatics, engineering, statistics, or a related field either at the time of application or be working towards the PhD.
Application Requirements
Curriculum Vitae – Your most recently updated C.V.
Cover Letter – A cover letter with career motivations and why you are interested in joining the lab
Apply link:
https://recruit.ap.uci.edu/JPF09758
About UC Irvine
The University of California, Irvine is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories covered by the UC anti-discrimination policy.
As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct.
As a University employee, you will be required to comply with all applicable University policies and/or collective bargaining agreements, as may be amended from time to time. Federal, state, or local government directives may impose additional requirements.
Job location
The University of California, Irvine is an Equal Opportunity/Affirmative Action Employer advancing inclusive excellence. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories covered by the UC nondiscrimination policy.
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