UNIV - Postdoctoral Scholar - Department of PHS

Medical University of South Carolina • Charleston, SC

1d • Onsite

About The Position

The Medical University of South Carolina (MUSC) is seeking a postdoctoral researcher in clinical AI and digital health to join the Division of Biomedical Informatics & AI, Department of Public Health Sciences, in Charleston. The research group uses real-world health data to develop tools to improve patient care across the lifespan. The postdoctoral scholar will work closely with Dr. Mamoun Mardini, contribute to ongoing lab projects, and build an independent research line within the lab's clinical AI program. Current research spans clinical language models for extracting information from unstructured EHR notes; machine-learning risk prediction using EHR data for clinical decision support; and wearables and mobile sensing, including passive sensing, ecological momentary assessment, and digital biomarkers of physical and cognitive function.

The role includes acquiring, curating, and preprocessing EHR, clinical notes, wearable, and mobile data; designing, training, and evaluating machine-learning, deep-learning, and language models; leading analyses and first-author publications; contributing to NIH grant proposals; collaborating on clinically meaningful outcomes and model validation; and helping mentor students.

Requirements

• PhD in biomedical informatics, computer science or engineering, data science, biomedical engineering, biostatistics, or a related field, or completion of the PhD before the start date.
• Strong programming skills in Python.
• Hands-on experience applying machine learning to real-world health data.
• A record of first-author publications and clear scientific writing.

Nice To Haves

• Experience with PyTorch or similar deep-learning frameworks.
• Experience with clinical NLP, transformer models, or LLMs, including fine-tuning, prompting, or retrieval-augmented generation.
• Experience with EHR data, wearable sensor data, or ecological momentary assessment.
• Familiarity with aging, frailty, or perioperative research.
• Interest in pursuing a K award or other early-career funding.

Responsibilities

• Acquire, curate, and preprocess EHR, clinical-note, wearable, and mobile data.
• Design, train, and evaluate machine-learning, deep-learning, and language models.
• Lead analyses and write first-author manuscripts for peer-reviewed journals and conferences.
• Present research findings at national meetings, such as AMIA, IEEE, and GSA.
• Contribute preliminary data and aims development for NIH grant proposals.
• Collaborate with others to define clinically meaningful outcomes and validate models.
• Help mentor graduate and undergraduate students in the lab.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree