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Position Announcement

The Department of Biological Sciences at Utah Tech University invites applications for a full-time, tenure-track Assistant Professor position in Computational Biology, with a primary focus on Next-Generation Sequencing (NGS) algorithms and their pedagogical application at both the undergraduate and graduate levels. This position is part of a two-position hire supporting the department's expanding programs in bioinformatics and genomics.

The successful candidate will be an expert in NGS algorithms and pipeline development, capable of translating complex computational concepts for students at varying levels of experience. The position will provide instruction for an existing Bachelor of Science in Bioinformatics and Master of Science in Genomics with a Bioinformatics emphasis.

The Biological Sciences department houses degree programs in Bioinformatics, Biological Sciences, Biomedical Sciences, Natural Sciences, and Biology Secondary Education. Additional program information is available at https://biology.utahtech.edu/.

Responsibilities

Cell Culture and Technical Support

• Maintain and expand cell lines (have to work during weekend as needed).
• Perform aseptic technique, passaging, cryopreservation, and thawing.
• Monitor and troubleshoot contamination (bacterial, fungal, mycoplasma).
• Support transfection, viral transduction, and other cell-based assays.
• Prepare media, reagents, and maintain cell culture documentation.
• Assist with experimental procedures including viability assays, microscopy, and molecular analyses.

Teaching and Curriculum

• Teach 24 credit hours of lower and/or upper-division courses per academic year across undergraduate and graduate levels.
• Deliver upper-division and master's-level courses in NGS algorithms, bioinformatics pipeline design, computational genomics, and related topics, with the ability to adapt instruction to students from both computational and life science backgrounds.
• Teach core NGS topics including short- and long-read sequencing platforms, read alignment algorithms (e.g., BWA, STAR, minimap2), variant calling, de novo assembly, transcriptomics, and epigenomics analysis.
• Develop and teach additional courses as needed, which may include Principles of Genetics, Introduction to Programming for Biologists, or Statistical Genomics, depending on departmental need and applicant expertise.
• Create innovative upper-level elective courses that reflect emerging areas of NGS technology and computational biology, complementing and diversifying the department's current offerings.
• Design and deliver instruction in multiple modalities including face-to-face, flipped classroom, hybrid, and fully online formats; willingness to teach evening and summer courses when needed.

Research and Mentorship

• Mentor master's students in functional genomics and NGS-focused research projects, guiding them from data generation through computational analysis and interpretation.
• Supervise undergraduate research in computational biology, providing hands-on experience with NGS datasets and bioinformatics workflows.
• Maintain an active scholarly profile consistent with the teacher-scholar model, including publications, presentations, or collaborative research appropriate to a primarily undergraduate and master's serving institution.
• Assist in mentoring and supervising part-time instructors teaching in the bioinformatics program.

Service and Institutional Contribution

• Collaborate with the Department Chair, Dean, and faculty colleagues on curriculum development, program assessment, and strategic planning for both the Bioinformatics B.S. and Genomics M.S. programs.
• Perform campus-wide service duties including holding regular office hours, attending department and division meetings, serving on university and college committees, and participating in outreach and recruitment activities.
• Contribute to interdisciplinary curricular and scholarly activities within the Department, the College of Science, Engineering & Technology, and the University.
• Perform other duties as assigned.

Qualifications

Required

• PhD in Computational Biology, Bioinformatics, Genomics, Computer Science with a biological application focus, or a closely related field.
• Demonstrated expertise in NGS algorithms and the analysis of high-throughput sequencing data, with proficiency in at least one scripting/programming language (Python, R, Bash, or equivalent) and familiarity with bioinformatics tools and workflow management systems (e.g., Snakemake, Nextflow).
• Successful teaching experience at the college or university level, with evidence of effective instruction of NGS and computational biology topics to students from diverse disciplinary backgrounds.
• Demonstrated ability to design and deliver innovative curriculum using a variety of instructional approaches, including active learning, project-based learning, and computational lab environments.
• Commitment to inclusive excellence: ability to work respectfully and collaboratively with students and colleagues from all backgrounds, and demonstrated advocacy for women, people of color, first-generation students, and other groups underrepresented in computational sciences.
• Strong written and oral communication skills, including the ability to explain complex algorithmic concepts clearly to non-expert audiences.
• Demonstrated capacity for continuous professional development, including staying current with rapidly evolving NGS technologies, tools, and best practices.

Preferred

• Postdoctoral or industry experience applying NGS methods in a research context.
• Experience teaching or mentoring in a bioinformatics, genomics, or data science program at the graduate level.
• Familiarity with cloud computing environments (AWS, Google Cloud, or equivalent) and high-performance computing clusters for large-scale genomics analyses and workflow management tools (Nextflow, Snakemake).
• Experience developing online or hybrid bioinformatics courses, including the design of computational lab modules and auto-graded assessments.
• Track record of interdisciplinary collaboration bridging computational and experimental biology.
• Strong commitment to the teacher-scholar model at a primarily undergraduate institution (PUI).