We have one Postdoctoral Research Fellow position immediately available in the Genetics and Multi-omics Core (GMC) of the Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases (Biggs Institute) at The University of Texas Health Science Center at San Antonio (https://biggsinstitute.org/). We are one of 33 centers in the nation and the only one in Texas recognized as a National Institute on Aging-designated Alzheimer’s Disease Research Center (ADRC).
The selected candidate will work primarily with Drs Xueqiu Jian and Bernard Fongang to analyze large-scale phenotypic, genetic and multi-omics data in a collaborative research setting of international studies on dementia and cerebrovascular diseases to identify novel biology and druggable targets underlying Alzheimer disease, vascular cognitive impairment, and resilience in cognitively normal super-agers. While working primarily on the data from our ADRC, the Framingham Heart Study (FHS), Texas Alzheimer's Research and Care Consortium (TARCC), and UK Biobank, the selected candidate will have access to data from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, the Trans-Omics for Precision Medicine (TOPMed) program, the Alzheimer’s Disease Sequencing Project (ADSP), the International Genomics of Alzheimer’s Project (IGAP). High performance and cloud computing research facility is available to perform large-scale data analysis. Under the supervision of the Biggs Institute Director and GMC Leader, Dr. Sudha Seshadri, the selected candidate is expected to identify his/her own core areas of interest, lead publications, work within a multi-disciplinary team, submit and win training grants and be ready to transition to faculty positions, typically in 2-3 years.
Salary will be based on NIH standard and commensurate with experience.
The candidate should have a background in biostatistics, genetic epidemiology, statistical genetics, bioinformatics or related fields, and are expected to be fluent in Linux and R. Other computing languages such as Python are a plus. Prior experience with large-scale biological datasets, multi-omics integration, genome-wide association studies, or machine learning is advantageous but not essential for an otherwise strong candidate. The candidate should have excellent problem-solving and communication abilities and is expected to keep his/her works well-organized and transparent.
Please apply by contacting Dr. Xueqiu Jian with a current CV.