Research Assistant in Laboratory Medicine & Pathology

University of Minnesota; Minneapolis (MN); On-site; USD 33,000 - 47,000; Part time

Job summary

The University of Minnesota's Advanced Research and Diagnostic Laboratory (ARDL) in the Department of Laboratory Medicine and Laboratory is seeking a Graduate Research Assistant to analyze aging-related data and develop ML-based prediction models using multi-omics and clinical datasets.

The role emphasizes statistical analysis, data integration, and bioinformatics pipelines for NGS data, with opportunities to contribute to manuscripts and presentations.

Qualifications

• Currently enrolled graduate student in statistics, biostatistics, data science or related field at University of Minnesota.
• At least 1 year experience performing statistical analysis using SAS and R.
• Ability to work effectively in a team with strong communication skills.
• Creative and critical thinking with attention to detail and research compliance.
• Ability to manage data from various sources and maintain organization.

Responsibilities

• Perform statistical analysis on large datasets addressing aging-related hypotheses (dementia, diabetes, CKD, etc.).
• Develop computational models to integrate high-dimensional omics data and build ML-based prediction models.
• Develop bioinformatics QC/analysis pipelines for NGS data.
• Assist in preparing reports, manuscripts, and presentations.
• Conduct literature reviews and perform other assigned duties.

Skills

SAS

R

Teamwork

Critical thinking

Data management

Education

Graduate student status at UMN

Tools

Python

PyTorch

Job description

About the Job

Dr. Vivek's lab in the Advanced Research and Diagnostic Laboratory (ARDL) in the Department of Laboratory Medicine and Laboratory is seeking to hire a graduate research assistant. Her research focuses on identifying blood-based biomarkers of aging and age-related outcomes. Also she focuses on analyzing and integrating high dimensional genomics and molecular data to develop ML-based prediction models to classify various health outcomes and to evaluate progression of disease. Biomarkers of interest can range from large multi-omics (whole genome sequencing, DNA methylation, RNA-Seq, metabolomics, proteomics, microbiome etc.) to individual proteins/analytes that are commonly measured in the clinical lab. Datasets from several ongoing large population-based cohorts with detailed biomarker and outcome data are available for analysis.

Job description:

• Perform statistical analysis on large datasets to address specific hypothesis related to aging and age-related outcomes such as dementia, diabetes, CKD etc.
• Develop computational models to integrate high dimensional omics data and develop ML-based prediction models
• Develop bioinformatics pipeline for QC and analysis of NGS data
• Assist in the preparation of reports, manuscripts, and presentations of research dissemination, as needed
• Perform literature reviews on assigned projects.
• Other duties as assigned

Qualifications

Required Qualifications:

• Currently enrolled University of Minnesota graduate student in statistics, biostatistics, data science or related field
• At least 1 year experience performing statistical analysis using SAS and R
• Demonstrated ability to work effectively interpersonally and professionally in a team
• Ability to think creatively and critically
• Strong attention to detail and ability to ensure research compliance
• Ability to manage data from various sources
• Excellent organizational skills

Preferred Qualifications:

• Masters students
• Prior experience in managing and analyzing large scale data from epidemiological or clinical trial studies
• Comfortable to develop ML models using Python, Pytorch etc.

Pay and Benefits

Pay Range: $28.93/hour; depending on education/qualifications/experience

Please visit the Office of Student Health Benefits website for more information regarding benefit eligibility.

Student workers are eligible to participate in the Student Health Benefit Plan, if they maintain 6 or more eligible course credits within a given semester. The same applies for Undergraduate Students, Graduate Assistants, Residents, Fellows and Interns.

Diversity

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

Employment Requirements

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.

About University of Minnesota

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.