Dartmouth College

What you'll study

The Computational Mathematics pathway combines core mathematical theory with practical computational techniques. Undergraduates typically complete a sequence in multivariable calculus and linear algebra, courses in real analysis and abstract algebra to build foundational theory, and targeted offerings in numerical analysis, scientific computing and mathematical modelling. Coursework often includes probability and statistics, differential equations, optimisation, and electives linking mathematics with computer science such as algorithms, data structures and machine learning.

Students are encouraged to undertake project-based work and a senior capstone or thesis that emphasises computation — for example, large-scale numerical simulation, data-driven modelling, or algorithm development for scientific problems. Many students also complement their study with programming languages (Python, MATLAB, C/C++), high-performance computing, and domain electives in engineering, economics, biology or physics to apply computational methods to real problems.

Entry requirements

Admission to Dartmouth is selective and based on a holistic review of academic preparation, letters of recommendation, and personal qualities. Successful applicants to the mathematics major typically have a strong record in secondary school mathematics, including calculus where available, and demonstrate quantitative reasoning ability. Preparation in a programming language or experience with computational projects is advantageous for the computational track.

Typical preparation includes:

• High school mathematics through calculus (or equivalent); advanced coursework such as AP or IB higher-level maths is beneficial.
• Evidence of analytical work: problem-solving competitions, research projects, or mathematics-related extracurriculars.
• Demonstrable interest in computing or data science (courses, independent projects, or internships) is recommended for students pursuing the computational emphasis.

Career prospects

Graduates with a computational mathematics background are well placed for roles that require quantitative and programming expertise. Common career paths include data science and analytics, quantitative finance and risk modelling, software engineering, scientific and engineering computation, and roles in technology companies. Employers value the ability to translate mathematical models into efficient algorithms and to analyse complex data.

Many alumni also go on to graduate study in applied mathematics, computer science, statistics, operations research, engineering or finance. The programme’s emphasis on project work and thesis preparation supports both industry entry and academic research careers.

Why study at Dartmouth College

Dartmouth offers a strongly undergraduate-focused environment with small class sizes and close faculty mentorship, which benefits students engaging in mathematically rigorous and computationally intensive work. Undergraduates have access to interdisciplinary centres such as the Neukom Institute for Computational Science and can take advantage of collaborations with the Thayer School of Engineering and other departments to pursue applied projects.

The college’s flexible academic calendar supports internships, research experiences and off-campus opportunities that allow students to gain practical computational experience. Faculty-led research, senior theses, and hands-on course projects are commonplace, providing a pathway from classroom learning to impactful computational work.