Georgia Institute of Technology

What you'll study

The Applied Mathematics curriculum emphasises mathematical modelling, analysis, and computation. Students take core courses in calculus, linear algebra, differential equations, real analysis and probability and statistics, then move into applied tracks that cover numerical analysis, optimisation, scientific computing, dynamical systems, mathematical modelling and partial differential equations.

• Core mathematical foundations: single- and multivariable calculus, linear algebra, differential equations, discrete mathematics and introductory real analysis.
• Applied and computational courses: numerical methods, scientific computing, numerical linear algebra, computational modelling, and programming for mathematicians (commonly using languages such as Python, MATLAB or C).
• Modelling and application areas: dynamical systems and chaos, continuum and PDE modelling, stochastic processes, optimisation and control theory, and mathematical finance or actuarial modules where available.
• Statistics and data science: probability, mathematical statistics, inference, machine learning foundations and data analysis electives to support careers in data-driven fields.
• Electives and specialisation: electives allow concentration in topics such as computational biology, fluid mechanics modelling, network science, signal processing or financial mathematics.
• Capstone and research opportunities: students complete a culminating project or practicum that applies mathematical tools to a real-world problem; many students undertake research with faculty, participate in undergraduate research programmes, or join interdisciplinary teams across engineering and computing.

Entry requirements

Admission to Georgia Tech is competitive. Successful applicants typically demonstrate strong achievement in secondary-level mathematics and science. Typical preparation includes completion of calculus and related advanced maths courses where available, with additional coursework in physics or computing desirable.

• Academic preparation: advanced secondary mathematics (including calculus), strong grades across a broad curriculum, and evidence of quantitative ability.
• Recommended subjects: calculus (including multivariable if available), algebra, statistics, physics and computer science or programming.
• Standardised tests and credentials: applicants present their home country secondary-school credentials; international applicants also meet university English language requirements. Georgia Tech evaluates applications holistically and considers coursework, examinations, personal statements and extracurricular achievements.
• Transfer and internal admissions: students already at Georgia Tech may apply to the Applied Mathematics programme following departmental procedures, often demonstrating suitable performance in initial mathematics and sciences coursework.

Career prospects

Graduates with a degree in Applied Mathematics are prepared for a wide range of careers where quantitative analysis and modelling are central. The programme’s strong computational component makes alumni attractive to employers across industry and research.

• Data science and analytics: roles in data engineering, machine learning, predictive analytics and business intelligence.
• Technology and software: algorithm design, scientific computing, simulation and software development for technical applications.
• Engineering and physical sciences: modelling, simulation and analysis roles in aerospace, mechanical, civil and biomedical engineering contexts.
• Finance and actuarial science: quantitative finance, risk analysis, investment modelling and actuarial careers.
• Research and academia: further study at master’s and PhD level in mathematics, applied mathematics, computational science or related fields, leading to research or university careers.
• Government and consulting: quantitative consulting, operations research, policy modelling and technical roles in government labs and agencies.

Why study at Georgia Institute of Technology

Georgia Tech is recognised for its strong emphasis on quantitative science, computation and engineering, creating an environment where applied mathematics is tightly integrated with real-world problem solving. The Institute provides access to interdisciplinary research centres, high-performance computing resources and collaborative projects with engineering, computing and science departments.

• Interdisciplinary opportunities: easy collaboration with engineering, computer science, physics and quantitative biology programmes, enabling applied projects across multiple domains.
• Research and experiential learning: ample undergraduate research opportunities, capstone projects and industry partnerships that let students apply mathematical methods to practical problems.
• Location and industry links: proximity to Atlanta’s technology, finance and research communities facilitates internships, co-operative experiences and industry engagement.
• Computational resources and faculty expertise: faculty with strengths in numerical analysis, modelling, data science and applied probability, together with access to modern computing facilities and software tools.