We are seeking a dedicated and innovative Postdoctoral fellow to work on the standardization of laboratory test names and laboratory test stewardship. Laboratory test names vary widely among hospitals and can be confusing. The work of this position will be aligned with the goals of TRUU-Lab, a national initiative to generate laboratory tests names that are easily understood by clinicians, and which reduce medical errors. Optimized names will be created through analysis of clinician survey data, by testing order names in mock EMR systems, and by the utilization of artificial intelligence (AI) and large language models to generate novel names that follow standard best practices. This position also entails writing papers and grants that will further our mission of helping clinicians order the right laboratory test, at the right time, for the right patient. This position is currently for 12 months, and could be extended further contingent on grant support.
- Collaborates with the TRUU-Lab team, consisting of healthcare professionals, CDC, FDA, EMR vendors, instrumentation vendors, programmers, and computer scientists to advance projects related to laboratory test name standardization.
- Designs, conducts, and analyzes experiments related to laboratory test ordering.
- Helps create standardized laboratory test names that can be used nationally.
- Helps create test naming guidelines.
- Applies statistical techniques to interpret research data from test naming surveys.
- Supervises the collection of data from Electronic Medical Records (EMR) databases.
- Collaborates with AI experts to use large language models to generate better test names.
- Plays an active role in the development of grant proposals.
- Prepares research findings for publication.
- Stays current with relevant advancements in laboratory medicine and data science by attending seminars
- MD or Ph.D. in Basic Science, Health Science, or a related field.
- No experience required.
- Ph.D. in Data Science, or fields related to Laboratory Medicine (Clinical Chemistry, Microbiology, etc.); Doctorate in Clinical Laboratory Science (DCLS), or MD or equivalent.
- Strong research background with a track record of relevant publications.
- Proficiency in statistical analysis, and use of R, SPSS, SAS software and data visualization tools.
- Experience working with electronic medical records.
- Strong background in laboratory medicine and test utilization highly desirable.
- Familiarity with artificial intelligence and machine learning concepts.
- Excellent communication skills, both written and verbal.
- Demonstrated ability in grant writing and securing research funding is a plus.
- Highly motivated, organized, and capable of working independently. Effective teamwork and collaboration skills.
Baylor College of Medicine is an Equal Opportunity/Affirmative Action/Equal Access Employer.