Master in Department of Mathematical Sciences

At Ulsan National Institute of Science and Technology (UNIST), the tuition fee is 5,415 USD per year.

Mathematical Sciences covers the study of abstract and applied mathematics, including analysis, algebra, probability, statistics, and computational methods. Students in this field build rigorous problem-solving skills through the study of mathematical structures and proofs, while also applying mathematical models to problems in science, engineering, finance, and data analysis. Coursework typically includes advanced topics chosen from areas such as differential equations, numerical analysis, statistics, or discrete mathematics, alongside training in mathematical reasoning and research methods. Graduates commonly pursue careers as data analysts, statisticians, quantitative researchers, or continue toward doctoral study and academic careers in mathematics or related quantitative fields. This master's program in Mathematical Sciences is offered by Ulsan National Institute of Science and Technology (UNIST) in Ulsan, South Korea. It spans four semesters, with intakes in March and August, and courses are taught in English. Students typically hold undergraduate degrees in mathematics, statistics, or a related quantitative field, and use the graduate program to deepen their expertise in a chosen area of mathematics through advanced coursework and research. Graduate mathematics programs generally emphasize independent research alongside coursework, with students working closely with faculty to explore open problems or apply mathematical methods to questions in other scientific disciplines. UNIST's setting as a science and technology-focused institution supports interdisciplinary work, where mathematical methods are applied to problems in engineering, physics, and data science. As demand grows across industries for advanced quantitative and analytical skills, graduate training in mathematical sciences prepares students for research and analytical roles in academia, technology, finance, and other data-driven fields.