Casual Computational Research Assistant

The Computational Research Assistant will support the development, testing, validation, and documentation of computational tools for genomic and cytogenetic research within the Department of Laboratory Medicine and Pathology. The position will implement established design specifications for genomic data processing and visualization and will evaluate approaches for identifying non-human contamination and contamination-related artifacts in sequencing data. The role requires familiarity with genomics, careful scientific reasoning, the ability to work independently from written specifications, and effective use of GitHub and AI-assisted computational-development tools.

Work Arrangement:
* The position is expected to work remotely more than 50% of the time. Your dedicated office space will be in your remote work location.
* The Department retains the right to modify flexible work arrangement agreements on a temporary or permanent basis for any reason at any time.

Work Schedule:
Approximately 10 hours per week on average, with a flexible schedule arranged around academic commitments and project needs.

Responsibilities:
60% - Implement and Test Computational Genomics Software
* Implement computational tools from established design specifications using AI-assisted development tools and other appropriate computational resources.
* Continue development and testing of software for parsing, representing, converting, and analyzing ISCN cytogenetic nomenclature.
* Develop and refine approaches for visualizing cytogenetic and genomic findings using CyDAS and related tools.
* Implement computational methods for detecting and characterizing non-human contamination in sequencing data.
* Develop approaches for identifying genomic variant calls that may result from contamination, mapping artifacts, or other technical sources rather than true human variation.
* Use GitHub for version control, issue tracking, code review, and management of project artifacts.
* Test software implementations and correct identified defects.
20% - Evaluate and Validate Genomic Analysis Methods
* Evaluate contamination-detection and filtering approaches using representative sequencing datasets.
* Design and conduct controlled analyses, including simulated or spike-in contamination experiments when appropriate.
* Compare computational predictions with known sample composition, expected genomic findings, and manually reviewed results.
* Evaluate how bacterial, viral, mammalian, and other non-human sequence contamination affects alignment and variant-calling results.
* Assess the performance and limitations of ISCN parsing, conversion, and visualization methods across representative cytogenetic examples.
* Identify problematic cases, false-positive findings, and methodological limitations and communicate these findings to the project team.
10% - Document Software, Methods, and Results
* Maintain documentation describing algorithms, software behavior, data structures, testing procedures, and known limitations.
* Record important scientific and implementation decisions and the rationale for those decisions.
* Summarize experimental results, unresolved questions, and recommended next steps.
* Maintain sufficient documentation to allow other laboratory personnel to reproduce analyses and continue development.
10% - Coordinate with the Research Team
* Meet with the supervisor and collaborators as needed to review specifications, progress, experimental findings, and next steps.
* Incorporate scientific and technical feedback into software implementations and experimental analyses.
* Communicate unexpected results, methodological concerns, and questions requiring additional scientific input.
* Coordinate work with related genomics, cytogenetics, contamination-detection, and visualization projects within the laboratory.

All required qualifications must be documented on application materials.
Required Qualifications:
* Current enrollment in an undergraduate or graduate degree program in computer science, data science, biology, genetics, bioinformatics, or a related field. Enrollment may be outside the University of Minnesota at a different institution.
* Familiarity with genetics, genomics, or genomic data.
* Familiarity with GitHub or similar version-control and collaborative-development tools.
* Familiarity with AI-assisted coding or software-development tools.
* Ability to independently implement work from detailed written specifications.
* Ability to systematically evaluate computational results and document findings.
* Ability to communicate clearly about technical and scientific work in a remote working environment.

Preferred Qualifications:
* Familiarity with biomedical research.
* Interest in bioinformatics, sequence-quality assessment, genomic contamination, or cytogenetics.
* Familiarity with next-generation sequencing data or genomic variant analysis.
* Familiarity with cytogenetic nomenclature or chromosome-level genomic data.
* Experience using large language models or other AI-assisted tools for software development, analysis, or documentation.
* Familiarity with genomic analysis tools, databases, or visualization software.
* Experience contributing to collaborative projects using GitHub.

Pay Range: $22.00/hour; depending on education/qualifications/experience.

Retirement plan options are available for Civil Service, Faculty, Labor-Represented, Professional & Administrative, and Temp Casual classifications. Learn more about retirement plans.

Applications must be submitted online. To be considered for this position, please click the Apply button and follow the instructions. You will be given the opportunity to complete an online application for the position and attach a cover letter and resume.

Additional documents may be attached after application by accessing your "My Job Applications" page and uploading documents in the "My Cover Letters and Attachments" section.

To request an accommodation during the application process, please e-mail jobcentr@umn.edu.

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.