"POSTDOCTORAL SCHOLAR POSITION: GENERATIVE AI FOR HEALTH AND MEDICINE (SHAH LAB)"

Position Overview

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 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 develops novel deep learning and AI-based technologies for digital biopsies from medical images and 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 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 manuscript review will be provided. For more information, visit: https://faculty.sites.uci.edu/pratikshahlab/ or https://www.pratiks.info/.

Key Research Areas:

• Generative AI for Medical Imaging and Digital Biopsies: Develop and interpret deep neural networks 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 and generate diagnostic tools for clinical use.
• Generative and Predictive AI for Clinical Decision Support and Statistical Inference: Develop biologically informed statistical methods and uncertainty estimation models to train deep learning models for clinical decision-making from electronic medical records (EMRs) and genetic sequencing data. Focus on predicting patient outcomes and discovering novel disease subtypes.

Responsibilities:

• Collecting, preprocessing, and visualizing high-dimensional medical images, non-imaging clinical (EMR), and genetic sequencing datasets
• Training and validating generative deep learning models (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
• Demonstrating strong analytical, organizational, and communication skills
• Committed to mentoring and teaching

Department:

https://medschool.uci.edu/research/clinical-departments/pathology-laboratory-medicine

Qualifications:

Basic qualifications: PhD or MD, PhD in computer science, biomedical informatics, engineering, statistics, or a related field.

Application Requirements:

Document requirements: Curriculum Vitae and Cover Letter with career motivations and interest in joining the lab. Reference requirements: Contact information for 3 references.