Develop large language models and other methods and tools to effectively use electronic health record (EHR) data; apply ML methods (especially deep learning methods) to solve critical medical problems.

Implement methods into software that meets research needs, manage and update source codes as needed.  Work in an interdisciplinary team of informaticists, programmers, information quality experts, statisticians, and researchers during software development.

Participate in design, implementation, and reporting of research and evaluation studies. Contributions to scientific reports, conference papers and journal articles are expected, including documentation of method, presentation of data, and participation in interpretation of results.

Participate in collaborative projects, contribute to the data processing, software development, and other collaborative efforts.

A Ph.D. in biomedical informatics, computer science or a related field. Working experience with large language models, data science using EHRs, machine learning, data mining, and natural language processing are preferred.

Ph.D. in Computer Science, Biomedical Informatics, or related field.  Experiences in natural language processing, large language models, machine learning (deep learning), and software development are preferred. Excellent formal and interpersonal communication skills, and the ability to communicate effectively to a broad range of audiences such as faculty members, PIs.


• Python, Java, or similar language experience.


• Familiar with popular machine learning packages, e.g., Pytorch.