Casual Computational Research Assistant

Summary

The University of Minnesota is a public research university supporting genomic and cytogenetic research. The Computational Research Assistant will develop, test, validate, document, and analyze computational tools for genomic data processing, cytogenetic visualization, and detection of non-human contamination in sequencing data.

Responsibilities

• 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
• 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
• 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
• 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

Skills

• 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
• 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

Qualifications

Must Haves

• 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

Nice to Haves

• 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

Benefits

• The position is expected to work remotely more than 50% of the time.
• Approximately 10 hours per week on average, with a flexible schedule arranged around academic commitments and project needs.
• Retirement plan options are available for Civil Service, Faculty, Labor-Represented, Professional & Administrative, and Temp Casual classifications.