Casual Computational Research Assistant

About the Job

The Computational Research Assistant will support the development, testing, validation, and documentation of computational tools for clinical and research genomics within the Department of Laboratory Medicine and Pathology. The position will primarily implement established design specifications for genomic data integration, analysis, querying, and visualization using modern computational and AI-assisted software-development tools. The role requires familiarity with genomics, careful attention to scientific and clinical requirements, the ability to work independently using written specifications, and effective documentation and communication.

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.

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

• 60% - Implement and Test Computational Genomics Software
  • Implement software from established design specifications using AI-assisted development tools and other appropriate computational resources.
  • Develop and refine components of a unified genomics data and visualization platform.
  • Integrate genomic information from multiple clinical and research sources into common data structures and queryable databases.
  • Implement analysis and visualization workflows for repeat expansions, chromosome and cytogenetic findings, FISH results, whole-genome sequencing variants, and copy-number variants from genomic arrays.
  • Develop and refine graphical interfaces and visualization tools for reviewing and interpreting genomic findings.
  • Use Git Hub for version control, issue tracking, code review, and management of project artifacts.
  • Test software implementations and correct identified defects.
• 20% - Validate Genomic Analyses and Software
  • Evaluate computational tools using representative genomic and clinical datasets.
  • Compare software output with expected results, reference data, and established interpretations.
  • Perform systematic testing of genomic data-processing, querying, and visualization workflows.
  • Identify discrepancies, edge cases, and limitations and communicate findings to the project team.
  • Support validation of repeat-expansion analysis and other genomic interpretation workflows before broader clinical or research use.
• 10% - Document Software, Decisions, and Results
  • Maintain clear documentation describing software behavior, data structures, workflows, testing procedures, and known limitations.
  • Record important implementation decisions and changes to established specifications.
  • Prepare concise summaries of completed work, unresolved issues, and recommended next steps.
  • Maintain sufficient documentation to allow other laboratory personnel to continue development and testing.
• 10% - Coordinate with the Research and Clinical Team
  • Meet with the supervisor and project collaborators as needed to review specifications, progress, and results.
  • Incorporate feedback from computational, laboratory, and clinical collaborators into software implementations.
  • Communicate technical problems, unexpected findings, and questions requiring scientific or clinical decisions.
  • Coordinate work with related computational genomics projects within the laboratory.

All required qualifications must be documented on application materials.

• 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 Git Hub 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 test work, identify problems, and document results.
• Ability to communicate clearly about technical and scientific work in a remote working environment.

• Familiarity with biomedical research.
• Interest in clinical genomics, molecular pathology, or computational pathology.
• Experience working with genomic sequence, cytogenetic, or other molecular laboratory data.
• Experience using…