Nowadays, there is mathematics in virtually everything, from mobile phones to passenger cars and oil tankers. The internet is built on mathematics. Google is based on probability theory, and cryptology and secure data transfer are based on classical number theory. Modern physics, chemistry, climate science, bioinformatics — the list is long.

American University’s Master of Science in Statistics is an excellent way to further your mathematical education, prepare for a doctoral program, or gain the expertise to advance your career. In this program, you will develop proficiency in the development, research, and analysis of quantitative tools to turn ideas into intelligent, informed actions. Incoming students can qualify for merit awards as Graduate Assistants or Research Assistantships to gain experience. We offer two different tracks to help you match your course of study to your intellectual and professional goals. The mathematical statistics track is for those intending to pursue a Ph.D. in statistics, while the applied statistics track is perfect for those intending to use their statistical expertise in the workplace. Whichever track you follow, AU’s MS in Statistics is your key to success.

In the Master's Program in Computational Physics, you will learn how to translate a mathematical model of a physical phenomenon into a robust computer program and then how to analyze the results from your calculations. You will study courses in programming, and mathematical and numerical methods and deepen your knowledge of physics.

Create innovative computing solutions, mathematical models, and dynamic systems to solve problems in industries such as engineering, biology, and more.

The MSc in Mathematics and Computing for Finance is designed to meet the demand for specially trained mathematicians in the world’s finance and insurance markets.

The Master of Science degree in Computational Science (MCS) at the Università della Svizzera italiana (USI) offers students the opportunity to acquire an in-depth understanding and set of skills in computational science, involving numerical simulation, applied mathematics, statistics, and data science. It provides an innovative combination of methodological and applied competencies in both computational and data science, which endow students with the knowledge and skills that are needed to operate at the forefront of science and industry.

This master’s course aims to respond to the demand for data scientists with the skills to develop innovative computational intelligence applications, capable of analysing large amounts of complex data to inform businesses decisions and market strategies. The main theme throughout this course is automatic big data analytics and natural language processing through machine learning, especially deep neural networks.

The Master of Science (MSc) program in Modelling and Computational Science takes advantage of the interdisciplinary nature of the Faculty of Science and collaborating faculties to offer students a program of study that introduces them to all aspects of the modelling process. The university's membership in the Shared Hierarchical Research Computer Network (SHARCNET), the Southern Ontario Smart Computing Innovation Platform (SOSCIP) and the advanced local computing infrastructure provides access to state-of-the-art computational facilities.

The Master of Science in Mathematical and Computational Sciences at the University of Prince Edward Island is designed to enhance students' expertise in mathematics, statistics, and computer science. This interdisciplinary program emphasizes both theoretical and applied aspects of these fields, fostering skills in problem-solving, data analysis, and computational techniques.

The MS in Computational & Applied Mathematics trains you in the analytical and numerical methods of applied mathematics to address and solve pressing challenges in all areas of science and engineering. Mathematical modeling and scientific computing have become increasingly useful problem-solving tools. You’ll learn analytical and numerical methods of applied mathematics, applying them to problems in physics, biology, engineering, economics, climate science, and more.

This course focuses on the mathematical modelling and computational techniques used in the financial industry, and on the required background in finance. Financial mathematics is a branch of mathematics where advanced mathematical and statistical methods are developed for and applied to financial markets and financial management. Its main aims are to quantify and hedge risks in the financial marketplace. Effective computational methods are crucial for the successful use of mathematical modelling in finance. This course is designed to reflect this combination of knowledge and skills so that graduates are well equipped to enter the competitive job markets of quantitative finance and related fields. Optional modules equip graduates with foundations of data analytics.

Applied and Computational Mathematics (A.C.M.) is an interdisciplinary program of graduate study. A.C.M. involves both mathematics and a partner discipline such as engineering, biological science, chemistry, sustainable energy or physics, and other diverse fields.

In addition to being a science in its own right, mathematics plays a fundamental role in the quantitative areas of practically all other academic disciplines, particularly in the natural sciences, engineering, business administration, economics, medicine, and psychology. Mathematical results permeate nearly all facets of life and are a necessary prerequisite for the vast majority of modern technologies – and as our IT systems become increasingly powerful, we are able to mathematically handle enormous amounts of data and solve ever more complex problems.

The main aim of the program is to provide the students with effective knowledge that they can successfully apply both in mathematical modelling and in the solution of problems arising in practice.