University of Nebraska Kearney

What you'll study

This degree blends core undergraduate mathematics with specialised computational courses. You will study foundational subjects such as calculus, linear algebra, abstract algebra and real analysis alongside applied and computational topics including numerical analysis, scientific computing, numerical linear algebra, ordinary and partial differential equations, mathematical modelling and optimisation.

• Core mathematical foundation: Calculus sequence, Linear Algebra, Differential Equations, Real Analysis, Probability and Statistics.
• Computational and applied courses: Numerical Analysis, Scientific Computing, Numerical Methods for PDEs, Computational Linear Algebra, Computational Modelling, Algorithms and Complexity.
• Programming and tools: Instruction and practice in programmable environments such as Python, MATLAB and/or C/C++, plus training in version control and scientific computing libraries.
• Electives and breadth: Options commonly include Data Science, Mathematical Optimisation, Discrete Mathematics, Mathematical Biology, and elective computer science modules to support algorithmic skills.
• Capstone experience: A senior project, research thesis or practicum that integrates mathematical theory and computational implementation, often with opportunities for collaboration with faculty or external partners.

Entry requirements

Applicants are expected to hold a high school diploma or equivalent. Strong preparation in mathematics—typically including algebra, geometry and precalculus or calculus—is required. Admissions commonly consider your overall academic record and strength of quantitative courses.

• Recommended background: Completion of calculus or an introductory college-level mathematics course, and prior exposure to problem solving or programming where possible.
• English language: Competence in academic English as demonstrated by institutionally accepted qualifications for non-native speakers.
• Placement and advising: New students may take mathematics placement tests to determine the appropriate starting courses. Transfer applicants will have credits assessed and are advised on course planning to meet degree requirements.

Career prospects

Graduates with a computational mathematics emphasis are prepared for roles that require quantitative reasoning, numerical modelling and programming. Common career paths include data analyst, quantitative analyst, software developer, computational scientist, operations research analyst and roles in engineering and finance that use simulation and optimisation.

• Industry roles: Analytics and data science positions, scientific and engineering modelling, software development for technical applications.
• Research and graduate study: Many graduates progress to master's or doctoral programmes in applied mathematics, computational science, statistics, computer science or engineering.
• Public sector and teaching: Opportunities in government labs, research institutes, education and technical consulting.

Why study at University of Nebraska Kearney

The University of Nebraska at Kearney offers a supportive undergraduate environment with relatively small class sizes and accessible faculty in the Department of Mathematical Sciences. The programme emphasises hands-on computational training, undergraduate research and projects that let students apply numerical methods to real problems.

• Undergraduate focus: Close faculty mentoring, opportunities for independent study and supervised research that are well suited to students seeking practical experience before entering the workforce or graduate study.
• Computing resources: Access to departmental computing facilities and software commonly used in scientific computing and data analysis.
• Career support: Advising and connections to internships and local employers in the region, plus resources for preparing for graduate applications and technical careers.