Why Study Scientific Computing?
Turn data, models, and code into scientific insight. Scientific Computing helps students apply computational tools to real-world challenges in science, engineering, and mathematics.
Solve Real Scientific Problems
Apply computational tools to questions in physics, biology, mathematics, engineering, and other STEM disciplines.
Build Technical Skills That Transfer
Develop programming, modeling, simulation, and data analysis skills valued in research, graduate study, and technical careers.
Learn Through Research
Work alongside faculty and peers on computational projects that connect classroom concepts to real scientific investigations.
What You’ll Study
Learn how scientists use computation to understand systems, analyze data, and test ideas. Coursework combines programming, mathematics, and modeling techniques with applications across the natural sciences and engineering.
In Demand-Skills:
- Scientific programming (Python, MATLAB, and related tools)
- Computational modeling and simulation
- Numerical methods
- Data analysis and visualization
- Quantitative problem-solving
Comprehensive Curriculum
Students complete 20 credit hours, with courses in programming, applied mathematics, and computational methods, along with advanced electives in modeling, simulation, or data science applications.
The minor works well with majors in:
Mathematics, computer science, and engineering science, or fields in physics and biology.
It’s a good fit for you if you:
- Want to use computation to solve complex scientific and real-world problems.
- Are interested in programming, data analysis, and mathematical modeling.
- Want experience that combines theory, coding, and applied problem-solving.
- Are considering careers connected to software development, data science, or scientific research.
Recent Graduate Careers
Scientific Computing prepares you to use computation as a tool for discovery, analysis, and innovation. Graduates apply these skills in research laboratories, technology organizations, healthcare systems, and graduate programs across STEM disciplines.
Scientific Research and Discovery
Use computational methods to model systems, analyze large datasets, and support scientific investigation.
Data and Computational Analysis
Transform complex data into actionable insights through modeling, visualization, and quantitative analysis.
Software and Technical Development
Build computational tools and software solutions that support research, engineering, and scientific applications.
Graduate Study and Advanced STEM Training
Continue developing expertise through graduate study in computer science, applied mathematics, engineering, data science, computational biology, and related fields.
Get Your Questions Answered
Students interested in the Scientific Computing minor should:
Talk with an academic adviser about how the minor fits into their degree. Explore introductory courses Review the course catalog for detailed requirements.