LER.me

Make All Learning Count.

Get Connected

  • What is a LER?
  • FAQs (opens in new tab)
  • Partner with Us
  • Visit EBSCOed (opens in new tab)

View our Policies

  • Accessibility (opens in new tab)
  • Standards (opens in new tab)
  • Terms of Use (opens in new tab)
  • Privacy Policy (opens in new tab)
  • Opt out (opens in new tab)

Get the app

Get it on Google PlayDownload on the App Store

© 2026 All rights reserved.

Powered by EBSCOed

Skip to main contentSkip to footer
  • Live Data
My LER
My LER
  1. Programs
  3. Bioinformatics

Bioinformatics

University of Utah

Bachelor's DegreeAcademic

Become a contributor for free to openly demonstrate student outcomes, industry alignment & eligibility criteria.

The Bioinformatics degree program in the Department of Mathematics will provide students with the education necessary to succeed in this growing and dynamic field. Building off a core group of mathematics, biology, and computer science courses, students will engage deeply with real-world problems as they chart their path through the degree program.

Credits

120 credits

Format

In-Person

Loading Skills & Competencies
Program Pathways

Credentials this program stacks toward

No program pathways.

Loading What You'll Learn
Program Details

Detailed information about this program

No detailed information available.

Requirements

What you need to earn this credential

No requirements listed.

Financial Aid

Eligible funding programs

No funding information available.

Scholarships

No scholarships listed.

Visit Program Website
Locations

Where this program is offered

  • Utah

    Utah

Loading Student Outcomes
Related Programs

Programs related to this one

No related programs.

Skills & Competencies

Skills developed through this program

Auto-populated·from O*NET via SOC 19-1029.01

Skills

Reading ComprehensionCritical ThinkingComplex Problem SolvingActive ListeningSpeakingWritingScienceJudgment and Decision Making

Knowledge

BiologyComputers and ElectronicsMathematicsEnglish LanguageChemistry

Abilities

Written ComprehensionWritten ExpressionOral ComprehensionOral ExpressionProblem SensitivityDeductive ReasoningInductive ReasoningInformation OrderingFluency of IdeasMathematical Reasoning

Tasks

  • Develop new software applications or customize existing applications to meet specific scientific pro
  • Communicate research results through conference presentations, scientific publications, or project r
  • Create novel computational approaches and analytical tools as required by research goals.

Technology

Analytical or scientific softwareData base user interface and query softwareObject or component oriented development softwareData base management system softwarePortal server software

Tools

Computer data input scannersComputer laser printersDesktop computersLaptop computersPersonal computers

Work Values

IndependenceAchievementRecognitionWorking ConditionsSupportRelationships
Career Pathways

Occupations this program prepares you for

Auto-populated·from O*NET + BLS
Occupations matched to this program, with median wage, top wage, growth, and openings
SOCOccupationMethodWageGrowthOpenings
Match confidence: medium19-1029.01Bioinformatics Scientiststitle_inference———
What You'll Learn

Key competencies developed through this program

Auto-populated·from NSX Competency Framework

Mastery: proficient (Level 3)(based on Bachelor's Degree)

  • Novel computational algorithms for sequence analysis or structural prediction — design, implement, and benchmark autonomously to address research goals that exceed the capability of existing published tools.
  • Complex multi-omics datasets spanning genomics, transcriptomics, and proteomics — integrate and interpret across full analytical scope to generate actionable biological insights for clinical or translational research programs.
  • Custom bioinformatics applications — architect and develop end-to-end using object-oriented or functional programming frameworks, deploying on cloud or HPC infrastructure with robust documentation and version control.
  • Interdisciplinary research teams including wet-lab scientists, clinicians, and computational staff — consult with autonomously to diagnose analytical problems, evaluate technology-based solutions, and guide study design decisions.
  • Peer-reviewed scientific publications and conference presentations — author and deliver as lead or corresponding scientist, translating complex computational findings for broad life-science audiences.
  • Multi-terabyte genomic databases and data warehouses — design, optimize, and govern using advanced DBMS and portal server technologies to support institution-wide research data needs.
  • Emerging biochemical assays and bioinformatics software releases — critically evaluate for methodological rigor, rapidly adapt laboratory workflows, and mentor junior staff on adoption strategies.
  • Analytical or scientific software platforms — customize and extend through API integration and enterprise application integration tools to meet highly specific and non-routine research requirements.
  • Systems-level evaluation of computational pipelines — perform to assess performance, reproducibility, and biological validity across diverse datasets and experimental conditions in a high-stakes research environment.
  • Mathematical modeling and statistical inference frameworks — apply with full autonomy to develop quantitative hypotheses and validate predictions against experimental molecular biology data.

Some details on this page are auto-populated from public workforce data sources: O*NET (opens in new tab), BLS (opens in new tab), College Scorecard (opens in new tab), DOL Training Provider Results (opens in new tab), NSX (opens in new tab). Provided in partnership with LER.me Career Intelligence.

Student Outcomes

Performance metrics for this program

Completion Rate
Not reported
Placement Rate
Not reported