How to Apply
Please submit your resume and letter of interest to Vanessa David ([email protected]), Faculty Affairs Liaison for the Department of Emergency Medicine
Job Summary
The Department of Emergency Medicine is seeking an Assistant Research Scientist with expertise in data science, clinical informatics, machine learning, and artificial intelligence (including large language models) to support collaborative, data-driven healthcare research initiatives. This position will focus on the application of advanced analytic and AI methods to clinical and health system data to support observational studies, quality improvement initiatives, and externally funded research projects.
The Assistant Research Scientist will work closely with faculty investigators, clinicians, and research staff to design, implement, and interpret analyses that advance patient-centered outcomes, operational efficiency, and innovation in emergency and acute care delivery. Independent research leadership is not required; this role is intended for a scientist who thrives in a team-based, collaborative research environment and contributes substantively to shared scholarly output.
Responsibilities*
Collaborate with faculty investigators and interdisciplinary research teams to support clinical, translational, and health services research using data-driven and AI-enabled approaches
- Extract, manage, and analyze complex clinical datasets, including electronic health record (EHR) data, administrative datasets, and research registries
- Apply statistical, machine learning, deep learning, and informatics methods, including large language models (LLMs) and natural language processing (NLP), to derive insight from structured and unstructured healthcare data
- Develop, fine-tune, and evaluate AI/ML models to support research questions related to clinical outcomes, operations, workflow efficiency, and decision support
- Design analytic plans; perform data cleaning, validation, and feature engineering; and maintain reproducible, well-documented analytic workflows
- Contribute to the preparation of abstracts, manuscripts, reports, and grant applications, including drafting or supporting methods and results sections
- Participate in interdisciplinary research meetings and provide data science, informatics, and AI expertise to clinical and research stakeholders
- Assess model performance, interpretability, and potential bias, and support responsible and ethical use of AI in healthcare research
- Ensure compliance with institutional and regulatory requirements related to data privacy, security, IRB approval, and human subjects research
- Support continuous improvement of data infrastructure, analytic tools, and best practices for clinical and AI-enabled research
Required Qualifications*
Doctoral degree (PhD, DrPH, ScD) with substantial relevant experience in data science, biostatistics, biomedical/clinical informatics, epidemiology, computer science, AI, or a closely related field
- Demonstrated experience working with clinical or health-related data, including EHR or administrative datasets
- Proficiency in programming and analytic languages commonly used in research (e.g., Python, R, SQL)
- Experience applying machine learning methods, with exposure to NLP and/or large language models in a research or applied setting
- Record of peer-reviewed scholarly output appropriate to career stage, or strong evidence of emerging scholarly productivity
- Experience working effectively in collaborative, multidisciplinary research environments
- Strong written and verbal communication skills, with the ability to explain analytic methods and findings to clinical and non-technical audiences
- Familiarity with research compliance requirements (e.g., IRB processes, data governance, HIPAA), or willingness to develop this expertise.
U-M EEO Statement
The University of Michigan is an equal employment opportunity employer.