Research Assistant Professor, Non-Tenure Track

Ut Health   •  

Houston, TX

Industry: Education


Not Specified years

Posted 56 days ago

The Center for Health Security and Phenotyping (CHSP) at the School of Biomedical Informatics (SBMI), the University of Texas Health Science Center at Houston (UTHealth), a leading academic health center, seeks an exceptional candidate for a non-tenure track position at the assistant professor level in the areas of health security and phenotyping.

UTHealth is in the world-renowned Texas Medical Center (TMC), located in cosmopolitan Houston, Texas, the fourth largest city in the United States. SBMI currently offers PhD and Master's degrees; it also features certificate programs in biomedical and health informatics.

RESPONSIBILITIES: The successful candidate will be expected to plan, supervise, and direct research in security and phenotyping, as well as related areas. The candidate will provide technical expertise to lead in the development of study design, sample or data collection, pipeline development, data analysis, results interpretation, manuscripts, and grants. In addition, this position offers opportunities to supervise postdoctoral fellows and lead projects or team research initiatives. Collaborative research with other faculty in the CHSP, at SBMI, and across UTHealth, Rice University, and the Texas Medical Center (e.g., MD Anderson Cancer Center and Baylor College of Medicine, etc.) is strongly encouraged.

QUALIFICATIONS: The candidate should possess a doctoral degree in computer science, biomedical informatics, mathematics, statistics, or a related discipline. He/she is expected to have experience in both machine learning and data mining, with the capacity to apply that expertise to the medical informatics domain. Strong algorithmic development and programming skills are required for this position, as are excellent teamwork and communication skills. Representative tasks for this position may include developing computational phenotypes, drug repurposing research, and optimizing clinical workflows, among others.