> Markdown version of [/jobs/ext/2604981-rsch-pro-5-informatics](https://www.wearedevelopers.com/jobs/ext/2604981-rsch-pro-5-informatics). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Rsch Pro 5-Informatics - **Company:** University of Minnesota - **Location:** Minneapolis, MN, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Data Analysis, Databases, Logistic Regression, Regression Analysis, Information Technology - **Published:** August 11, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=ab1409db983bd2d5 ## About the Role Master's Degree in Epidemiology, Statistical Genetics, Population Genetics, Bioinformatics, or closely related field; at least three years of relevant post-bachelor's work and demonstrated skills in programming analyses of genome-scale data. Good interpersonal and communication skills (both oral and written) are also essential, as well as ability for setting priorities, multi-tasking, and working with several faculty researchers to meet numerous deadlines. Ability to provide datasets to collaborators and trainees, and to advise on analysis of these datasets., Experience with analysis of human genomic data. Familiarity with cancer epidemiology, sources of cancer data, and especially pediatric cancer data. Ability to obtain and analyze data from disparate sources to conduct integrative analyses. Conversance in non-genomic data and ability to integrate nongenomic data into genomic analyses. ## Description 70% conduct genomic analyses of pediatric cancer etiology and outcome at the direction of faculty members; this includes studies of germline genetic pleiotropy across pediatric cancers; post-GWAS analyses of data from the Admixture and Risk of Acute Leukemia (ADMIRAL) study; analysis of GWAS data for hepatoblastoma and Ewing sarcoma. Responsibilities include: * Processing raw genomic data, conducting routine QC, report QC results to supervisors * Independently obtain and match cases with publicly available control data * Lead logistic regression and other multivariable regression analyses using appropriate statistical genetic software including R, Plink, and SNiPAR. * Prepare manuscripts in collaboration with Epidemiology & Clinical Research faculty, figures, and written/oral reports for internal and external dissemination, including journal publications and conference presentations. * Lead bioinformatics efforts on collaborative projects within Pediatric Epidemiology, serving as a liaison across laboratories and providing strategic and technical guidance to enhance the impact of shared research goals. Candidate will be expected to collaborate with other investigators to enhance current projects and develop unique line of inquiry. * Provide intensive grant application support to faculty including technical sections, power calculations, figures, etc. 20% develop and document genomic analytic pipelines for use by Division students/trainees, including: * Pipelines for analyzing microsatellite repeats in long-read whole genome sequencing * Pipeline for integrative studies including expression, protein-level, and metabolome quantitative trait loci * Pipelines for analysis of family-based genetic data including relatedness-disequilibrium regression and de novo mutation detection 10% obtain and manage external genomic datasets such as from the Database of Genotypes and Phenotypes at the direction of faculty; duties include: * Maintaining IRB and other administrative approvals * Tracking data users to ensure compliance * Ensuring data erasure after study close. Program/Unit Description The Division of Epidemiology and Clinical Research has nearly a 30 year history of conducting epidemiologic research into the causes of childhood cancer, outcomes during treatment, and late effects among survivors. Currently three faculty work in this area, along with numerous graduate students and postdoctoral fellows. Data to be managed and analyzed include numerous genomewide variant array, whole exome, and whole genome datasets for multiple pediatric cancers. Division research and trainees are supported by multiple NIH and foundation grants, an NIH T32 training grant, and the generous philanthropy of the Children's Cancer Research Fund. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [May I interest you in ... 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