Dartmouth University

What you'll study

The programme emphasises mathematical modelling, computational methods and statistical thinking alongside core pure mathematics. You will build a foundation in calculus, linear algebra and differential equations before moving on to applied topics and methods used across industry and research.

• Core mathematics: multivariable calculus, linear algebra, ordinary differential equations and real analysis to give a rigorous base for applied work.
• Applied and computational courses: numerical analysis, scientific computing, mathematical modelling, optimisation and partial differential equations.
• Probability and statistics: probability theory, mathematical statistics, stochastic processes and data analysis for modelling uncertainty and inference.
• Interdisciplinary electives: options in computer science (algorithms, machine learning), physics, engineering, economics and biology to apply mathematical tools to other domains.
• Capstone / project work: a senior thesis or applied project that typically involves modelling a real problem, implementing numerical methods, analysing data and presenting results.
• Skills developed: analytical reasoning, mathematical modelling, numerical computation, programming (commonly Python, MATLAB or similar), data analysis and scientific communication.

Entry requirements

Admission to the undergraduate programme is through the university’s standard undergraduate application process. Successful applicants typically demonstrate strong achievement in high‑school mathematics and related subjects.

• Academic background: high school coursework in algebra, geometry, precalculus and preferably calculus; strong grades in quantitative subjects.
• Standardised tests and portfolio: the university’s current policy on standardised tests may vary—check the admissions pages for whether SAT/ACT are required or optional. Submitting a transcript that shows rigorous quantitative preparation is important.
• Supporting materials: personal statement, teacher/counsellor recommendations (especially from mathematics instructors) and any relevant extracurricular or research experience in maths, programming or science.
• Mature or international applicants: equivalent qualifications such as international exam scores or national certificates are considered; courses in advanced mathematics or evidence of programming and quantitative work strengthen an application.

Career prospects

Graduates with a bachelor’s in applied mathematics are prepared for a wide range of careers where quantitative and analytical skills are central. Many graduates go directly into industry or consulting, while others pursue graduate study.

• Data science and analytics: roles as data scientists, analysts or machine learning engineers in technology, healthcare and retail.
• Finance and risk: careers in quantitative finance, risk modelling, actuarial work and investment analysis.
• Engineering and technology: positions in software development, computational modelling, simulation and algorithm design.
• Research and graduate study: further study in applied mathematics, statistics, computer science, engineering or related fields leading to research or academic careers.
• Government and policy: roles involving statistical modelling, forecasting and quantitative policy analysis.

Why study at Dartmouth University

The programme is delivered in a small, undergraduate‑centred environment with close faculty supervision and opportunities for early involvement in research. Students benefit from an interdisciplinary culture that encourages collaboration with departments such as computer science, engineering, economics and the natural sciences.

• Hands‑on research: opportunities for senior theses and faculty‑mentored projects that connect theory to practical problems.
• Small class sizes: close interaction with faculty and peers, with access to seminars and specialised applied courses.
• Computing and laboratory resources: access to high‑performance computing facilities and software used in numerical and data‑intensive work.
• Career support and alumni network: dedicated career services, internships and a strong alumni network that can help with placements in industry and graduate programmes.