Human Genetics Data Analyst/Bioinformation - Nephrology

Columbia University
United States, New York, New York
Nov 04, 2024
Job Type: Officer of Administration Regular/Temporary: Regular Hours Per Week: 35 Salary Range: $65,000 - $90,000 The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training. The above hiring range represents the University's good faith and reasonable estimate of the range of possible compensation at the time of posting. Position Summary Our research focuses on human genetic studies related to kidney diseases, including investigations into kidney transplantation outcomes. We are seeking motivated, independent, and collaborative scientists with expertise in the statistical analysis of human genetic data, including GWAS, exome sequencing, or genome sequencing. This work directly impacts clinical medicine and will be conducted in close collaboration with other researchers in our group. Additionally, you may be involved in the analysis of genetic data generated by projects such as eMERGE (Electronic Medical Records and Genomics), UK Biobank, All-of-Us, KPMP (Kidney Precision Medicine Project), and the APOLLO (APOL1 Long-term Kidney Transplantation Outcomes) projects. Responsibilities Perform bioinformatic processing of genetic and transcriptomic data. Conduct genetic analyses as required for funded research projects. Contribute to collaborative projects within the lab. Supervise and mentor students, post-docs, or junior analysts. Perform other related duties as needed. Minimum Qualifications Bachelor's degree in bioinformatics, biostatistics, human genetics, computational biology, or a related field, or equivalent in education and experience, plus three years of related experience Advanced degree in in bioinformatics, biostatistics, human genetics, computational biology, or a related field would substitute for experience Prior experience in analyzing genetic association studies, including exome or genome sequence and RNA sequence data. Must be collaborative, capable of working in a fast-paced environment, and skilled at multitasking. Team orientation, excellent written and verbal communication skills, as well as strong creative thinking and problem-solving abilities. Proficiency in basic programming languages such as R, PERL, or PYTHON. Peer-reviewed publications in relevant research fields. Strong recommendations from 2-3 professional references (prior mentors or collaborators). Preferred Qualifications Familiarity with tools for genome and transcriptome interpretation. Knowledge of statistical principles and methods relevant to human genetics. Strong programming skills Other Requirements Successful completion of applicable compliance and system training requirements Equal Opportunity Employer / Disability / Veteran Columbia University is committed to the hiring of qualified local residents.