University of North Dakota
Research Assistant Professor, Biomedical Sciences
University of North Dakota, Grand Forks, North Dakota, United States, 58203
Research Assistant Professor, Biomedical Sciences
Job no:
497409 Work type:
Full-time Faculty Location:
Grand Forks Categories:
Non-Tenure-Track Faculty
$60,000-$80,000, Dependent on experience, annual
This position will work onsite the Grand Forks, ND campus.
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.
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.
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-cell or 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 Advertised:
15 Dec 2025 Central Standard Time
Applications close:
To assure full consideration, applications must be received by 12/26/2025 and include the following materials:
Current CV
Names and contact information for three professional references
#J-18808-Ljbffr
497409 Work type:
Full-time Faculty Location:
Grand Forks Categories:
Non-Tenure-Track Faculty
$60,000-$80,000, Dependent on experience, annual
This position will work onsite the Grand Forks, ND campus.
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.
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.
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-cell or 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 Advertised:
15 Dec 2025 Central Standard Time
Applications close:
To assure full consideration, applications must be received by 12/26/2025 and include the following materials:
Current CV
Names and contact information for three professional references
#J-18808-Ljbffr