Postdoctoral Researcher

We are recruiting highly ambitious and motivated Postdoctoral Researchers in the Division of Biomedical Informatics (BMI) within the Department of Health Outcomes and Biomedical Informatics (HOBI) at University of Florida (UF) with a focus on various aspects of data science, especially Artificial Intelligence and Machine Learning (AI/ML). The successful candidate should possess a Ph.D. in biomedical informatics, computer science, information science, data science, electrical engineering, computer engineering, or a related field. Preference will be given to applicants with prior experience in electronic health records (EHRs) data, general data science, machine learning, computer vision, and natural language processing (NLP). This position will involve collaborative efforts with a diverse group of stakeholders, including informatics experts, clinicians, basic scientists, and translational researchers within our department and across the University of Florida campus. The Postdoctoral Researcher will take the lead and provide support for tasks such as data mining on EHRs, development of ML methods, creation of software packages, scientific paper writing, and presentations at national/international conferences. Additionally, the Postdoctoral Researcher will actively participate in analysis and reporting projects, which include data summarization and visualization, and contribute to the analysis, modeling, and interpretation of results. The successful candidate is expected to work on research projects that:
(1) Utilize real-world data (RWD), including EHRs, in combination with AI/ML methods.
(2) Integrate RWD with other data sources, such as images and genomics, for outcomes research.
(3) Develop and apply innovative informatics or AI/ML methods, including NLP with large language models (LLMs).
(4) Develop and apply novel causal inference methods, especially causal AI methods.

Duties Include:

Develop methods and tools to effectively use electronic health record (EHR) data; apply ML methods (especially deep learning methods) to solve critical clinical and biomedical 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.

Lead and 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.

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

$56,484 - $58,000

A Ph.D. in biomedical informatics, computer science, electrical engineering, computer engineering, information science, data science, or a related field.

Working experience with electronic health records (EHRs) data, general data science, machine learning, computer vision, and natural language processing (NLP) are preferred.  Excellent formal and interpersonal communication skills, and the ability to communicate effectively to a diverse audience such as faculty members, PIs.


• Python, Java, or similar programming language experience.


• Working experience with popular machine learning packages, e.g., support vector machines (SVMs), conditional random fields (CRFs), Gradient Boosting Machines (GBM), deep learning methods.

In order to be considered, you must upload your cover letter and resume.

The University of Florida is committed to non-discrimination with respect to race, creed, color, religion, age, disability, sex, sexual orientation, gender identity and expression, marital status, national origin, political opinions or affiliations, genetic information and veteran status in all aspects of employment including recruitment, hiring, promotions, transfers, discipline, terminations, wage and salary administration, benefits, and training.

This is a time limited position.

Application must be submitted by 11:55 p.m. (ET) of the posting end date.