UNIV - Postdoctoral Scholar - Department of PHS

Medical University of South Carolina; Charleston (SC); On-site; USD 34,000 - 55,000; Full time

Job summary

The Medical University of South Carolina (MUSC) in Charleston invites applications for a postdoctoral researcher in clinical AI and digital health within the Division of Biomedical Informatics & AI, Department of Public Health Sciences. The role focuses on transforming real-world health data into tools to improve patient care and working closely with Dr.

Mamoun Mardini. Responsibilities include acquiring diverse data, developing ML/LLM models, publishing first-author work, and contributing to

Qualifications

• PhD (or completion before start) in biomedical informatics, computer science/engineering, data science, biomedical engineering, biostatistics or a related field.
• Strong programming skills in Python; experience with PyTorch or similar deep learning frameworks.
• Hands‑on experience with machine learning on real‑world health data.
• A record of first-author publications and clear scientific writing.
• Experience with clinical NLP, transformer models or LLMs (fine‑tuning, prompting, 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 notes, wearable and mobile data, and design, train and evaluate machine learning, deep learning and language models.
• Lead analyses and first-author manuscripts for peer-reviewed journals and conferences, and present findings at national meetings (e.g., AMIA, IEEE, GSA).
• Contribute to NIH grant proposals, including preliminary data and aims development.
• Work with collaborators to define clinically meaningful outcomes and validate models.
• Help mentor graduate and undergraduate students in the lab.

Skills

Python

PyTorch

ML on health data

First-author publications

Clinical NLP

LLMs/Transformers

EHR data familiarity

Data preprocessing

Education

PhD in biomedical informatics / CS / data science / related field

Tools

PyTorch

Job description

Job Description Summary

We are seeking a postdoctoral researcher in clinical AI and digital health to join our research group in the Division of Biomedical Informatics & AI, Department of Public Health Sciences, at the Medical University of South Carolina (MUSC) in Charleston. We turn real-world health data into tools that improve care for patients across the lifespan. The postdoc will work closely with Dr. Mamoun Mardini.

Our current work spans three connected areas:

Clinical language models: extracting clinical information from unstructured EHR notes with domain-specific transformer models and LLMs.

AI risk prediction from real-world data: machine learning models built on EHR data for clinical decision support.

Wearables and mobile sensing: passive sensing, ecological momentary assessment and digital biomarkers of physical and cognitive function.

Entity

Medical University of South Carolina (MUSC - Univ)

Worker Type

Employee

Worker Sub-Type

Regular

Cost Center

CC001038 COM PHS Operations CC

Pay Rate Type

Hourly

Pay Grade

University-00

Pay Range

0.00 - 0.00 - 0.000

Scheduled Weekly Hours

40

Job Description

The postdoc will contribute to ongoing lab projects and build an independent research line within the lab's clinical AI program.

Job Duties:

• 35% Acquire, curate and preprocess EHR, clinical notes, wearable and mobile data, and design, train and evaluate machine learning, deep learning and language models.
• 25% Lead analyses and first-author manuscripts for peer-reviewed journals and conferences, and present findings at national meetings (e.g., AMIA, IEEE, GSA).
• 10% Contribute to NIH grant proposals, including preliminary data and aims development.
• 20% Work with collaborators to define clinically meaningful outcomes and validate models.
• 10% Help mentor graduate and undergraduate students in the lab.

Preferred Qualifications:

• PhD (or completion before the start date) in biomedical informatics, computer science/engineering, data science, biomedical engineering, biostatistics or a related field.
• Strong programming skills in Python; experience with PyTorch or similar deep learning frameworks.
• Hands‑on experience with machine learning on real‑world health data.
• A record of first-author publications and clear scientific writing.
• Experience with clinical NLP, transformer models or LLMs (fine‑tuning, prompting, 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.

Additional Job Description

Physical Requirements: (Note: The following descriptions are applicable to this section: Continuous - 6-8 hours per shift; Frequent - 2-6 hours per shift; Infrequent - 0-2 hours per shift) Ability to perform job functions in an upright position. (Continuous) Ability to perform job functions in a seated position. (Continuous) Ability to perform job functions while walking/mobile. (Frequent) Ability to climb stairs. (Infrequent) Ability to work indoors. (Continuous) Ability to work in all cold temperature extremes, i.e. spot coolers. (Frequent) Ability to bend at the waist. (Frequent) Ability to twist at the waist. (Frequent) Ability to perform 'pinching' operations. (Continuous) Ability to fully use both hands/arms. (Continuous) Ability to perform repetitive motions with hands/wrists/elbows and shoulders. (Continuous) Ability to fully use both legs. (Continuous) Ability to reach in all directions. (Continuous) Possess good finger dexterity. (Continuous) Ability to maintain tactile sensory functions. (Continuous) Ability to maintain good olfactory sensory function. (Continuous) Ability to lift and carry 15 lbs., unassisted. (Frequent) Ability to lift objects, up to 15 lbs., from floor level to height of 72 inches, unassisted. (Frequent) Ability to lower objects, up to 15 lbs., from height of 72 inches to floor level, unassisted. (Frequent) Ability to push/pull objects, up to 15 lbs., unassisted. (Infrequent) Ability to lift and carry objects up to 15 lbs. a distance of five (5) floors and to outlying buildings. (Frequent) Ability to maintain 20/40 vision, corrected. (Continuous) Ability to see and recognize objects close at hand. (Continuous) Ability to see and recognize objects at a distance. (Continuous) Ability to match or discriminate between colors. (Continuous) Ability to determine distance/relationship between objects; depth perception. (Continuous) Good peripheral vision capabilities. (Continuous) Ability to maintain hearing acuity, with correction. (Continuous) Ability to perform gross motor functions with frequent fine motor movements. (Continuous) Ability to be qualified physically (by medical personnel) for respirator use, initially and annually. Ability to work alone in isolated areas, such as darkrooms. (Frequent) Additional New Requirements: Ability to obtain and maintain a valid drivers license. Computer literacy. Ability to work rotating shifts as required. Ability to work overtime as required. Ability to learn and use new processes, tools and equipment as required.

If you like working with energetic enthusiastic individuals, you will enjoy your career with us!

The Medical University of South Carolina is an Equal Opportunity Employer. MUSC does not discriminate on the basis of race, color, religion or belief, age, sex, national origin, gender identity, sexual orientation, disability, protected veteran status, family or parental status, or any other status protected by state laws and/or federal regulations. All qualified applicants are encouraged to apply and will receive consideration for employment based upon applicable qualifications, merit and business need.

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