Postdoctoral Associate

Postdoctoral Associate

The Division of Biomedical Informatics and Data Science within the Department of Health Outcomes and Biomedical Informatics (HOBI) at the University of Florida (UF) is seeking a highly motivated postdoctoral researcher with a strong background in biomedical informatics, artificial intelligence, machine learning, or data science. The successful candidate will join a collaborative and interdisciplinary research team to contribute to cutting-edge research at the intersection of AI/ML, real-world data, and health outcomes.

Ongoing projects leverage large-scale multimodal clinical data, including electronic health records (EHRs), medical imaging, genomics, wearable devices, and unstructured clinical text, to develop novel methods for disease prediction, precision medicine, and clinical decision support.

Applicants must have a Ph.D. in biomedical informatics, computer science, data science, biomedical engineering, statistics, or a related STEM field. Experience with EHR data, machine learning or deep learning, natural language processing, medical imaging, or large language models (LLMs) is highly desirable. Familiarity with causal inference, real-world evidence, multimodal data integration, or cloud/high-performance computing is a plus.

The postdoctoral researcher will collaborate closely with biomedical informaticians, clinicians, statisticians, and translational researchers across the University of Florida. Responsibilities include developing and evaluating AI/ML methods, analyzing large-scale clinical datasets, building computational tools and software, preparing manuscripts for publication in high-impact journals, presenting research at scientific conferences, and contributing to NIH and other federal grant proposals. The position offers excellent opportunities to lead research projects, publish extensively, develop new methodological expertise, and establish an independent research program within a highly collaborative and well-funded research environment.

Required qualifications include:

• Ph.D. in biomedical informatics, computer science, data science, biomedical engineering, statistics, biostatistics, or a related quantitative STEM field.
• Strong programming skills in Python and/or R; experience with SQL and Linux/Unix is desirable.
• Demonstrated research experience in biomedical informatics, artificial intelligence (AI), machine learning, or data science, including the analysis of large-scale biomedical or healthcare datasets (e.g., electronic health records, medical imaging, genomics, or other real-world data).
• Excellent written and oral communication skills.
• Ability to work effectively in a collaborative, multidisciplinary research environment.

Preferred experience includes:

• Experience working with electronic health records (EHRs), real-world data (RWD), clinical data warehouses, or other healthcare databases.
• Experience developing and applying machine learning, deep learning, natural language processing (NLP), computer vision, or large language models (LLMs) for biomedical or healthcare research.
• Experience integrating and analyzing multimodal data, including structured EHR data, clinical text, medical imaging, genomics, wearable devices, or other biomedical data sources.
• Familiarity with causal inference, statistical learning, clinical prediction modeling, or real-world evidence methodologies.
• Experience developing reproducible research software, computational pipelines, or open-source tools using modern software engineering practices (e.g., Git/Git Hub, Docker, workflow management).
• Evidence of scholarly productivity through peer-reviewed publications and presentations at scientific conferences.
• Experience working on NIH-funded or other federally funded research projects and contributing to grant proposal development.

Special instructions to applicants:
In order to be considered, you must upload your cover letter and resume. Application must be submitted by 11:55 p.m. (ET) of the posting end date.

Health assessment required:
No