Master of Social Work - Traditional
The traditional Master of Social Work (MSW) program at the University at Buffalo is des...
M.S. in Computational and Applied Mathematics
Buffalo, New York
INTAKE: Jan & Aug
Program Overview
The M.S. in Computational and Applied Mathematics at UB is a 33-credit hour program typically completed in 1.5 to 2 years, with an emphasis on preparing students for the 21st-century professional workforce. The program is structured around three flexible tracks: Applied Probability and Statistics, Computation (including high-performance computing, data-intensive computing, and data science), and Complex Systems (including network science). This allows students to tailor their studies to specific career interests while acquiring highly marketable techniques in areas like machine learning, data analysis, and traditional applied mathematics methods. The program only accepts students starting in the Fall semester.
Curriculum: The 33-credit M.S. program comprises seven required courses (21 credit hours), three electives (9 credit hours), and a final project (3 credit hours). Required courses provide a strong foundation in core areas such as "Probability Theory," "Introduction to Statistical Inference," "Introduction to Numerical Analysis I & II," "Fundamentals of Applied Mathematics I," and "Data-Oriented Computing." Students then select electives based on their chosen track (Applied Probability and Statistics, Computation, or Complex Systems). Examples of electives include "Mathematical Finance," "Network Theory," "Large Deviations Theory and Rare Event Simulation," "Advanced Numerical Analysis," and "Introduction to Machine Learning." The culminating final project allows students to apply their learned skills to a practical problem.
Research Focus: The M.S. in Computational and Applied Mathematics program at UB is deeply rooted in applying mathematical and computational methods to solve real-world problems. While it's a professional master's degree, the curriculum and faculty expertise support research-oriented learning. Research areas align with the program's tracks, focusing on areas like complex systems, network science, high-performance and data-intensive computing, and advanced statistical modeling. Students are trained to master computer tools for experimenting with mathematical concepts, implementing mathematical models, and analyzing data. The final project allows students to engage in a focused research effort under faculty guidance, contributing to solutions for contemporary challenges.
Industry Engagement: The UB M.S. in Computational and Applied Mathematics program is explicitly designed to meet the tremendous demand for a professional labor force skilled in its core competencies. The program's learning outcomes emphasize the ability to relate mathematical ideas and techniques to other disciplines and communicate results clearly to experts and non-experts, crucial skills for industry. Graduates are made "highly employable in various industries based locally, nationwide, and worldwide." While the program description doesn't detail specific internships or industry partnerships within the curriculum, the strong career focus and the relevance of the skills taught (data analysis, machine learning, statistical methods) ensure direct applicability to industry needs. The university's broader connections to businesses and entrepreneurs in the region and beyond further facilitate career opportunities.
Global Perspective: The M.S. in Computational and Applied Mathematics program at UB inherently possesses a global perspective due to the universal applicability of mathematics and computational science. The demand for professionals skilled in data analysis and applied mathematics is a global phenomenon, and the program aims to make graduates "highly employable in various industries based locally, nationwide, and worldwide." The mathematical tools and statistical methods taught are universally recognized and used in diverse international contexts. The University at Buffalo itself is a large, globally-minded institution with a diverse international student body and faculty, enriching the learning environment with varied global perspectives on complex problems. This ensures graduates are prepared to work on global challenges and collaborate with international teams.
Location
Buffalo, New York
Score
IELTS 6.5
Tuition Fee
USD 28210
Postgraduate Entry Requirements
Academic Qualifications: Applicants for postgraduate programs typically require a minimum academic achievement of 70% or above in their bachelor's degree.
English Language Proficiency:
- IELTS: Overall band score of 6.5 or 7.0 with a minimum of 6.0 in each component.
- TOEFL: Overall score of 90 or higher.
- PTE: Overall score of 61 or higher.
- DET (Duolingo English Test): Minimum score of 120.
The University at Buffalo (UB) offers a variety of scholarships and financial aid opportunities specifically aimed at supporting international students who wish to pursue their studies in the United States. These scholarships are designed to reward academic excellence, leadership, and community involvement, helping to make education more affordable for talented students worldwide.
Merit-Based Scholarships: UB provides competitive merit scholarships to outstanding international undergraduate and graduate students. Awards such as the International Student Academic Excellence Scholarship recognize high-achieving students based on their academic records, standardized test scores, and extracurricular involvement.
Graduate Fellowships and Assistantships: Graduate international students can apply for teaching assistantships, research assistantships, and fellowships which offer tuition remission and stipends. These opportunities allow students to gain valuable teaching and research experience while offsetting the cost of their education.
Departmental Scholarships: Many academic departments at UB offer scholarships tailored to students in specific programs or fields of study. These awards may consider academic merit, research interests, or financial need.
External Scholarships: UB encourages international students to explore external scholarship options from private organizations, governments, and international foundations that support study in the U.S. The university’s International Student Services office provides guidance on identifying and applying for such funding sources.
A Master of Science (M.S.) in Computational and Applied Mathematics from the State University of New York at Buffalo (UB) provides graduates with a robust blend of advanced mathematical theory, computational expertise, and statistical analysis skills. This program is highly valued for its focus on solving complex, real-world problems using quantitative methods, making its graduates exceptionally versatile and in-demand across numerous industries.
Data Scientist/Analyst: This is a rapidly growing field where graduates leverage their skills in statistical modeling, machine learning, and data-oriented computing to extract insights from large datasets. They work in technology, finance, healthcare, and consulting to inform business strategy, product development, and operational efficiency.
Quantitative Analyst (Quant): Highly sought after in the financial services industry, Quants use sophisticated mathematical models, statistical methods, and computational techniques to analyze financial markets, develop trading strategies, manage risk, and price complex financial instruments for investment banks, hedge funds, and asset management firms.
Operations Research Analyst: These professionals apply advanced mathematical modeling, optimization techniques, and statistical analysis to improve efficiency and decision-making within organizations. They work in logistics, supply chain management, healthcare, and government, optimizing processes, resource allocation, and forecasting.
Software Developer/Engineer (with Mathematical Focus): Graduates with strong programming and algorithmic skills can work in software development, particularly in areas requiring complex mathematical computations, such as scientific computing, machine learning platforms, data analytics tools, or specialized simulation software.
Research Scientist (Computational/Applied Mathematics): In academia, government labs, or R&D departments of major corporations, research scientists conduct theoretical and applied research, developing new mathematical models, algorithms, and computational methods to solve cutting-edge problems in various scientific and engineering disciplines.
Actuary: Actuaries use mathematics, statistics, and financial theory to assess and manage financial risk, primarily in the insurance and pension industries. They design insurance policies, determine premiums, and ensure the financial soundness of benefit plans. This career typically requires passing a series of professional exams in addition to the master's degree.
Machine Learning Engineer: Given the program's strong emphasis on data science and machine learning, graduates are well-positioned to design, build, and deploy machine learning models and algorithms. They work in tech companies, e-commerce, and any industry looking to leverage AI for predictive analytics, automation, or intelligent systems.
Bioinformatician/Computational Biologist: For those with an interest in life sciences, these roles involve applying computational and statistical methods to analyze biological data, such as genomic, proteomic, or clinical data. They work in biotechnology, pharmaceutical companies, and academic research to understand biological processes and accelerate drug discovery.
Environmental Modeler/Analyst: Graduates can apply their skills to environmental science, developing and running mathematical models to understand and predict environmental phenomena like climate change, pollution dispersion, or ecological dynamics. They work for environmental consulting firms, government agencies, or research institutions.
Consultant (Data/Analytics/Strategy): The problem-solving and analytical skills gained are highly transferable to consulting. Graduates can advise businesses across various sectors on data strategy, analytics implementation, process optimization, or strategic decision-making, leveraging their quantitative expertise to drive solutions.
