Background: Arizona Veterans Research and Education Foundation uniquely partners with the Phoenix Veterans Administration Health Services and is seeking a Postdoctoral Associate or Research Associate (depending on experience) to investigate the genetic basis of prostate cancer in veterans in the Million Veteran Program. Location: Remote Employment Type: 1099 independent contractor WOC Approval Process: The candidate must obtain a Without Compensation (WOC) appointment to work at the Phoenix VA. The WOC approval process involves several steps and requires approval from Veterans Affairs Administration. The process typically takes about 2-4 months. Position Description : The Postdoctoral or Research Associate will be responsible for conducting investigation on a possible recessive genetic etiology for prostate cancer using data from the Million Veteran Program under the supervision of project investigators and in collaboration with investigators at other institutions. Schedule: Full Time October 1, 2025- August 31, 2028 Study 1 : Title: Identification of recessive prostate cancer risk alleles in the Million Veteran Program Funding Agency: Department of Defense office of the Congressionally Directed Medical Research Programs (CDMRP) Site Lead: Robert J. Klein, Ph.D. Specific Duties : The person hired for this position will conduct a genetic investigation into recessive alleles associated with prostate cancer risk using the data resources of the Million Veteran Program. This person will work to develop the relevant phenotype in the MVP data. This person will identify the needed software, or use custom code in languages such as R or Python, to process the genetic and sequencing data and associate it with prostate cancer under a recessive model. This person will collaborate closely with researchers at the Icahn School of Medicine at Mount Sinai in New York on this project. This person will draft resulting manuscripts and present results at national meetings. Required Qualifications: Doctorate degree in genetics, computational biology, biostatistics or related field. Familiarity with computational analyses in a biomedical context using coding languages such as R or Python. Experience in human genetics studies is a plus

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