Biostatistician-Intermediate

Ut-Health-Science-Center-At-SAN-Antoni; San Antonio (TX); On-site; USD 80,000 - 110,000; Full time

Job summary

UT Health San Antonio's Population Neuroscience Core (PNC) within the Glenn Biggs Institute invites applications for a Biostatistician to support epidemiologic and population-based research on brain aging and Alzheimer's disease.

Reporting to the PNC leadership, you will design studies, implement statistical analyses, harmonize complex datasets, and contribute to publications and grant proposals. Collaboration with investigators, clinicians, and trainees is central to the role.

Job description

The Population Neuroscience Core (PNC) within the Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases at The University of Texas Health Science Center at San Antonio (UT Health San Antonio) is seeking an exceptional Biostatistician to join a dynamic, collaborative research team conducting cutting-edge research on brain aging and Alzheimer’s disease. This position is particularly well suited for a biostatistician or data analyst who enjoys working collaboratively with investigators and applying statistical methods to complex, real-world epidemiologic data.

The Biostatistician will provide statistical and data-analytic support across the Core’s portfolio of epidemiologic and population-based research programs. The position will work closely with faculty investigators, epidemiologists, clinicians, research staff, and trainees to design studies, develop and implement statistical analyses, manage and harmonize complex research datasets, interpret findings, and contribute to scientific publications and grant applications.

The PNC supports large-scale longitudinal cohort studies and collaborative research initiatives, including the San Antonio Heart and Mind Study (SAHMS), the South Texas Alzheimer’s Disease Research Center, MarkVCID, the Cross-Cohorts Consortium, and other national and international consortia. Our research datasets are richly phenotyped and may include longitudinal clinical and cognitive assessments, psychosocial measures, neuroimaging, biomarkers, genomic and other omics data, and wearable/sensor data.