Associate Professor – Internal Medicine (Medical Informatics)

University of Kansas Medical Center • Kansas City, MO

117d

About The Position

The Associate Professor in the Division of Medical Informatics within the Department of Internal Medicine plays a key role in advancing research through data science, biostatistics, and biomedical informatics. This position contributes to the development of informatics approaches that support studies in areas such as Medical Informatics, Sleep Medicine, Physical Activity and Weight Management, Nephrology, and Endocrinology. The role emphasizes collaboration with faculty across Internal Medicine, other academic units within the University, and senior leadership from affiliated organizations, including the University of Kansas Health System and the State of Kansas. By integrating computational methods with clinical and translational research, the position helps generate data-driven insights that inform both scientific discovery and improvements in patient care. The scope of this work supports interdisciplinary initiatives and strengthens institutional capacity for innovation in healthcare research.

Requirements

• Ph.D. in Biomedical Informatics, Computer Science, Data Science, Statistics, or a related field.
• Experience in machine learning, statistical learning, and data mining principles and practices.
• Experience in developing and validating predictive models using large-scale clinical data, particularly Electronic Health Records (EHRs) and claims databases as demonstrated by a record of peer-reviewed publications and funding.
• Experience in leading or managing complex, data-intensive, multi-site research projects requiring deep understanding of clinical data infrastructure and its use in research.
• A track record of involvement in externally funded projects as the Principal Investigator and strong publication record in peer-reviewed journals.

Nice To Haves

• Experience working within large clinical data research networks.
• Experience with cloud computing platforms (e.g., AWS, Azure, Databricks, Google Cloud) for scalable data analysis and infrastructure development.
• Experience in causal inference methods for observational data.
• Experience and working knowledge of SQL and R.
• Established track record in teaching and service.

Responsibilities

• Lead the design, development, and implementation of novel machine learning and statistical algorithms to analyze 'big' medical data.
• Develop and validate robust predictive and prescriptive models for various health outcomes, with an initial focus on chronic and acute diseases.
• Oversee the enhancement and management of a clinical data research infrastructure, including the integration of cloud computing capabilities.
• Provide informatics leadership and support for collaborative, multi-institutional research projects.
• Collaborate with a multidisciplinary team of clinicians, data scientists, and researchers to translate research questions into actionable analytical plans.
• Contribute to the writing of grant proposals to secure research funding from federal and private sources.
• Disseminate research findings through publications in high-impact journals and presentations at scientific conferences.
• Participate in training and education of graduate/doctoral students and post-doctoral fellows in research settings and in formal and informal group education formats.
• Contribute to committees at the University level that supports research and teaching mission.

Benefits

• Coverage begins on day one for health, dental, and vision insurance.
• Employer-paid life insurance and long-term disability insurance.
• Paid time off, including vacation and sick, begins accruing upon hire, plus ten paid holidays.
• One paid discretionary day is available after six months of employment.
• Paid time off for bereavement, jury duty, military service, and parental leave is available after 12 months of employment.
• A retirement program with a generous employer contribution and additional voluntary retirement programs (457 or 403b) are available.

What This Job Offers

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