University of Hawaii at Manoa

What you'll study

The programme emphasises numerical methods, scientific computing and the mathematical foundations needed for reliable computation. Core topics commonly covered include numerical linear algebra, numerical solution of differential equations (ODEs and PDEs), approximation theory, and computational optimisation. Students also study algorithm analysis, scientific programming and data structures, and may choose electives in areas such as dynamical systems, stochastic modelling, inverse problems, uncertainty quantification and high-performance computing.

Programme structure can be tailored as a predominantly coursework-based master's or a research-led master's with a thesis. Typical components include advanced coursework, a computational project or thesis supervised by faculty, and seminars. Practical work frequently involves implementation in languages and environments used in research and industry (for example Python, MATLAB, C/C++ and parallel computing frameworks), and methods for validating, benchmarking and scaling algorithms on modern computing platforms.

Typical modules and examples

• Numerical Linear Algebra
• Numerical Methods for Ordinary and Partial Differential Equations
• Scientific Computing and Algorithm Design
• Computational Optimisation
• Probability and Stochastic Methods for Computation
• High-Performance and Parallel Computing
• Advanced Topics: Inverse Problems, Data Assimilation, Machine Learning for Scientific Computing

Entry requirements

Applicants are normally expected to hold a bachelor’s degree in mathematics, applied mathematics, statistics, computer science, engineering or a closely related discipline, with evidence of strong performance in core mathematical subjects. Preparation in multivariable calculus, linear algebra, differential equations and introductory real analysis is normally expected, together with some programming experience.

Typical application materials include official academic transcripts, a statement of purpose describing research interests and goals, and letters of recommendation. International applicants must demonstrate English language proficiency by meeting the University of Hawaii at Manoa’s accepted test scores or exemptions. Specific departmental requirements (such as whether the GRE is considered) should be confirmed with the Mathematics Department at the time of application.

Career prospects

Graduates go on to careers in research and industry that require strong quantitative and computational skills. Common roles include computational scientist, numerical analyst, data scientist, scientific programmer, quantitative analyst in finance, and engineering analyst. The training is also suitable preparation for doctoral study in applied mathematics, computational science, engineering and related disciplines.

Alumni find employment in academic research groups, government and national laboratories, technology and engineering companies, finance and consulting firms, and organisations working on environmental science, oceanography and geophysical modelling—areas where large-scale numerical simulation and data-driven computation are important.

Why study at University of Hawaii at Manoa

The University of Hawaii at Manoa offers a mathematics programme located within a research-active campus with strengths in applied and computational disciplines. Students benefit from small cohorts and opportunities to work closely with faculty on computational projects that address locally and regionally relevant scientific problems. Interdisciplinary collaboration is encouraged, with accessible connections to departments such as computer science, engineering and the natural sciences.

The campus provides access to institutional computing resources and supports for parallel and scientific computing, along with seminars and colloquia that expose students to current research. Studying at UH Manoa also offers the chance to engage with research problems tied to the Pacific region, while gaining skills that are widely transferable to international research and industry roles.