Job Description

The University of Tennessee Health Science Center Department of Pediatrics Research seeks a highly motivated and innovative Postdoctoral Scholar. This position offers a unique opportunity to contribute to cutting-edge research at the intersection of artificial intelligence, machine learning, and healthcare. The successful candidate will develop and apply advanced machine learning techniques (e.g. explainable, ethical, empathic and agentic AI), natural language processing (NLP), large language models (LLMs), data science methods, and mHealth to analyze large-scale, multidimensional, and multimodal datasets. The goal is to generate predictive models that provide valuable causal and probabilistic insights into clinical and population health outcomes.

In addition to technical research responsibilities, the incumbent will play a key role in implementing and managing a multi-phase study designed to improve HPV vaccination uptake among adolescents.

1. Develops and applies advanced ML algorithms, NLP models, and LLMs to analyze complex data.
2. Designs and implements novel data science methodologies for predictive modeling, causal inference, and probabilistic analysis in clinical and population health contexts.
3. Conducts data mining and knowledge discovery from multidimensional and multimodal datasets.
4. Collaborates with a diverse team of researchers, clinicians, and public health experts to translate data insights into actionable outcomes.
5. Contributes to scientific publications, presentations, and grant applications.
6. Performs other duties as assigned.

Ph.D. in a relevant discipline (e.g. Medical Informatics, Computer Science, Data Science, Computational Social Science, Epidemiology, Biostatistics, etc.)

Strong research track record, programming, and implementation skills, along with excellent communication, organizational, and project management skills. Experience in both qualitative and quantitative research and studying and implementing public health interventions are highly desirable.