Computational Science.
Data details: Graduation rate, gender, ethnicity, and summary are for this specific degree (6-digit CIP) from IPEDS. Salary, debt, and related financial outcomes are based on the degree category (4-digit CIP) from the College Scorecard API. ← Back to search
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Please use your own discretion when interpreting these results. For certain degrees, a limited number of institutions report to the government's College Scorecard API, which may cause the data to be skewed or less representative of national trends. Consider these figures as informative but not definitive, and consult additional sources or advisors for important decisions.
Debt to Income Ratio
Why Computational Science. stands out: With a debt-to-income ratio of just 39.1%, graduates of this program typically enjoy manageable student loan payments compared to their first-year earnings. This low ratio means that, on average, students who complete Computational Science. can expect to pay off their student debt faster and with less financial stress than most other fields. Programs with a DTI below 0.5 are considered excellent by financial experts, making this degree a smart investment for your future.
For example, with a median salary of $69023 and average student debt of $27000, the financial outlook for Computational Science. graduates is especially strong in .
Key Insights
Computational Science. is a program that attracts motivated students who want to make an impact. Starting pay for new grads is typically $69023, and with an average debt of $27000, the debt-to-income ratio comes in at 0.39—meaning you’ll have lots of flexibility after graduation.
This program sees about 2167 graduates annually, so you’ll be joining a well-established network. A common next step is a career as a Computer Programmers, which is expected to see -6.0% growth. Whether you’re aiming for a high-paying job, a stable career, or a chance to make an impact, Computational Science. is a great foundation. Remember, your journey is shaped by the opportunities you pursue—so get involved and stay curious!
Degree Overview
Computational Science (CIP 30.3001) is an interdisciplinary STEM field focused on solving complex scientific and engineering problems using advanced computation, mathematics, and simulation. It sits at the intersection of computer science, applied mathematics, and domain sciences such as physics, chemistry, biology, engineering, and data science. This degree is designed for students who want to use computing not just to build software, but to model reality itself—simulating phenomena that are too large, too small, too fast, or too dangerous to study directly.
For a degree search site, Computational Science is a high-value, future-facing program aligned with modern research, industry, and national priorities. It appeals to students who enjoy math, coding, and scientific reasoning, and who want to work on problems like climate modeling, drug discovery, aerospace simulation, artificial intelligence, financial forecasting, and large-scale data analysis. The field emphasizes computation as a third pillar of science—alongside theory and experiment.
What Is a Computational Science Degree?
A Computational Science degree is an interdisciplinary program that trains students to use computers as scientific instruments. Instead of studying phenomena only through equations or physical experiments, students learn to build computational models that simulate real-world systems and generate predictions.
Students combine:
- Advanced programming and algorithms
- Numerical methods and applied mathematics
- Domain-specific scientific knowledge
Universities offer Computational Science programs to:
- Train professionals who can model and simulate complex systems
- Prepare students for high-performance computing (HPC) environments
- Support research in science, engineering, and data-intensive fields
- Develop graduates who can translate scientific questions into computational solutions
This degree is distinct from computer science because the primary goal is not software products, but scientific insight, prediction, and optimization.
What Will You Learn?
Students learn how to convert scientific problems into computational form, choose appropriate numerical methods, and interpret results critically. You’ll study how errors arise in simulations, how models are validated, and how computational limits affect conclusions.
Core Skills You’ll Build
Graduates typically develop skills such as:
- Scientific programming—writing efficient code for simulations and analysis
- Numerical methods—approximating solutions to equations that cannot be solved analytically
- Mathematical modeling—representing real-world systems computationally
- Data analysis and visualization—interpreting large simulation outputs
- High-performance computing (HPC)—parallel computing and cluster-based processing
- Algorithmic thinking—designing efficient computational solutions
- Error analysis and validation—understanding uncertainty and numerical stability
- Interdisciplinary collaboration—working across scientific domains
These skills are highly valued in research, industry, and government.
Topics You May Explore
Coursework varies by institution, but commonly includes:
- Numerical Analysis: solving differential equations and linear systems
- Scientific Computing: simulation techniques and computational workflows
- Applied Linear Algebra: matrix methods for large-scale problems
- High-Performance and Parallel Computing: distributed and GPU computing
- Modeling and Simulation: physical, biological, or economic systems
- Computational Physics, Chemistry, or Biology: domain-specific applications
- Data-Driven Modeling: combining simulation with data science
- Optimization Methods: improving efficiency, accuracy, or performance
- Visualization and Scientific Communication: presenting complex results clearly
What Jobs Can You Get With This Degree?
A Computational Science degree prepares students for highly technical roles that combine coding, math, and domain expertise. Many graduates pursue advanced degrees, but strong industry roles are also common.
Common career paths include:
- Computational Scientist: developing and running simulations for research or industry
- Data Scientist or Applied Scientist: combining modeling with large datasets
- Simulation Engineer: modeling physical or engineered systems
- Quantitative Analyst: modeling financial or risk systems
- Machine Learning or AI Engineer: applying numerical methods to intelligent systems
- Research Software Engineer: building scientific computing infrastructure
- Government or National Lab Researcher: working on large-scale scientific problems
- Graduate or PhD Path: pursuing advanced computational research
Where Can You Work?
Graduates work in environments that rely on advanced computation:
- National laboratories and research institutions
- Technology and software companies
- Aerospace and defense organizations
- Biotechnology and pharmaceutical firms
- Energy and climate research organizations
- Financial services and quantitative trading firms
- Universities and academic research centers
How Much Can You Earn?
Computational Science maps to high-paying technical careers due to its rarity and complexity.
Typical ranges include:
- Entry-level computational roles: often $75,000–$95,000
- Computational scientists or simulation engineers: commonly $95,000–$140,000
- Data science or AI-focused roles: often $110,000–$170,000+
- Senior or specialized experts: can exceed $180,000
Advanced degrees significantly increase earning potential.
Is This Degree Hard?
Computational Science is considered highly challenging. It requires comfort with advanced math, programming, and abstract scientific reasoning at the same time. Students must manage complex codebases, mathematical rigor, and domain-specific knowledge simultaneously.
However, for students who enjoy deep problem-solving and building models of reality, the difficulty is often motivating rather than discouraging.
Who Should Consider This Degree?
This degree may be a strong fit if you:
- Enjoy math, coding, and science equally
- Like solving problems that don’t have closed-form answers
- Are interested in simulation, modeling, or AI
- Want to work on cutting-edge scientific or technical challenges
- Are considering graduate school or research-oriented careers
How to Prepare in High School
To prepare for a computational science program:
- Take advanced math (calculus and beyond)
- Learn programming (Python, C++, or similar)
- Study physics, chemistry, or biology to build scientific context
- Practice problem-solving and algorithmic thinking
- Explore basic numerical or simulation concepts if possible
Computational Science (CIP 30.3001) is a cornerstone degree for the modern scientific world. It prepares students to use computation as a lens for discovery—turning raw equations and data into predictive models that drive innovation across science, engineering, medicine, and technology.
Personality Fit (RIASEC Profile)
Official assessment tool by the U.S. Department of Labor