Research Assistant Professor, Biomedical Sciences

Salary/Position Classification

• $60,000-$80,000, Dependent on experience, annual
• This position will work onsite the Grand Forks, ND campus.

Purpose of Position

The Research Assistant Professor in the Computational Data Analysis Core (CDAC) will collaborate with investigators across the Host Pathogen Interactions (HPI) COBRE and SMHS to apply advanced bioinformatic analysis techniques to a wide variety of data domains. They will also develop and maintain rigorous, reproducible analysis pipelines while conducting collaborative and independent scholarship to support the research mission. The Research Assistant Professor will prepare and submit independent and collaborative grant proposals and serve as PI/co PI/Co I on extramural applications as well as performing collaborative core-facing duties such as analyses, consultation, training, server coordination, figure/report generation. This is an in person and on premise position.

Duties & Responsibilities

• Bioinformatics Analysis & Core Support 
  • Analyze high-throughput datasets (bulk/single-cell/spatial transcriptomics, DNAmethylation/epigenomics, metagenomics/virome, viral variant sequencing, multi-omicsintegration). 
  • Design and implement standardized, containerized pipelines (e.g., nf-core, Nextflow;R/Python workflows) emphasizing reproducibility, QC, and FAIR data stewardship. 
  • Provide experimental design consultation; coordinate with sequencing service providers; assess data quality; translate results for investigators (reports, figures, methods).
  • Maintain organized project repositories and shared data structures enabling secure, easy access for labs and sponsors. 

• Research Development & Scholarly Activity 
  • Develop independent lines of computational research aligned with SMHS priorities. 
  • Prepare and submit grants to NIH/NSF/foundations; contribute to center/program renewals; lead or support multi-PI applications. 
  • Author/co-author manuscripts; present at scientific meetings; contribute to data- and methods-focused publications and preprints. 
• Training, Outreach & Teaching 
  • Train faculty, staff, and students in modern bioinformatics (workshops, SOPs, code templates, office hours). 
  • Mentor trainees on best practices (version control, workflow management, statistics, visualization, and reporting). 
• Computational Infrastructure & Compliance 
  • Partner with SMHS IT to sustain CDAC compute resources. 
  • Ensure compliance with IRB/DUA/NIH data-sharing and reproducibility guidelines; contribute to data management plans. 

Required Competencies

• Excellent written and verbal communication; ability to translate complex analyses for diverse scientific audiences.
• Demonstrated independence and teamwork in multi-disciplinary settings, strong client service orientation.
• Rapid learning of new tools; methodical problem-solving; commitment to reproducible research.

Minimum Requirements

• Ph.D. in Biomedical Sciences, Bioinformatics, Computational Biology, or closely related field.
• 5 years of post-degree experience conducting computational analysis of high-through put biological data in R and/or Python, including pipeline development and statistical modeling.
• 5 years proficiency with UNIX/Linux environments; version control (git);containerization/workflow tools (e.g., Docker/Apptainer, Nextflow).
• 5 years proficiency with at least one programming language, such as Python, Perl, Java,or C.
• Evidence of scholarly productivity in bioinformatics/biomedical data science with a minimum of 4 first/co-first author peer reviewed publications since 2020.
• Successful completion of a Criminal History Background Check

In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the US and to complete the required employment eligibility verification form upon hire.

Preferred Qualifications

• Experience with multi-omic integration (e.g., transcriptomics + epigenomics), single-cellor spatial transcriptomics, and/or metagenomics.
• Teaching/training experience (workshops, course modules, internal seminars); mentoring students/postdocs.
• Experience preparing publication-quality visualizations (e.g., Illustrator, ggplot2) and generating polished reports.

To Apply

To assure full consideration, applications must be received by 12/26/2025 and include the following materials:

• Cover Letter
• Current CV
• Official Transcript
• Names and contact information for three professional references