Rsch Pro 5-Informatics

University of Minnesota
Minneapolis, MN, United States
25 days ago
Apply on www.indeed.com
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Working hours
Regular working hours
Job source

Tech stack

Data Analysis Databases Logistic Regression Regression Analysis Information Technology

Job 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.

Requirements

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.

About the company

The University recognizes and values the importance of diversity and inclusion in enriching the employment experience of its employees and in supporting the academic mission. The University is committed to attracting and retaining employees with varying identities and backgrounds.

The University of Minnesota provides equal access to and opportunity in its programs, facilities, and employment without regard to race, color, creed, religion, national origin, gender, age, marital status, disability, public assistance status, veteran status, sexual orientation, gender identity, or gender expression. To learn more about diversity at the U: http://diversity.umn.edu

Any offer of employment is contingent upon the successful completion of a background check. Our presumption is that prospective employees are eligible to work here. Criminal convictions do not automatically disqualify finalists from employment.

The University of Minnesota, Twin Cities (UMTC)

The University of Minnesota, Twin Cities (UMTC), is among the largest public research universities in the country, offering undergraduate, graduate, and professional students a multitude of opportunities for study and research. Located at the heart of one of the nation’s most vibrant, diverse metropolitan communities, students on the campuses in Minneapolis and St. Paul benefit from extensive partnerships with world-renowned health centers, international corporations, government agencies, and arts, nonprofit, and public service organizations.

At the University of Minnesota, we are proud to be recognized by Forbes as a Best Employer for Company Culture (2026), Best Employer for Women (2023, 2025, 2026), and Best Employer by State (2022-2026). In 2026, we also received Culture Excellence & Industry Awards recognition for employee appreciation and work-life flexibility.

You must create an Indeed account before continuing to the company website to apply

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.indeed.com
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

3:30 min

Approaching data problems with an engineering and strategy mindset

Becky Gandillon · LIVE

4:16 min

Training logistic regression classification models in tensorflow.js

Thomas Reiter · LIVE

1:48 min

Automating exploratory data analysis within training pipelines

Dora Petrella · World Congress 2023

3:04 min

Database evolution and the funding behind vector databases

Erik Bamberg · LIVE

3:04 min

Pre-built algorithms and further learning resources

Ayon Roy · LIVE

1:36 min

Performing exploratory data analysis to uncover underlying patterns

Julian Joseph · LIVE

Videos

See all

Related articles

See all