Research Focus
- Mathematical analysis and applied mathematics, with an emphasis on the mathematical theory of partial differential equations, numerical analysis and the properties of solutions.
- Mathematical modelling, studying practical problems through theoretical analysis and computational methods, especially mathematical models related to physical systems, fluid mechanics, materials science and other fields.
- Innovative applications of mathematical methods and numerical algorithms, including algorithms and numerical techniques for simulating complex dynamic systems, especially multiscale modelling and computational methods.
- Interdisciplinary areas combining mathematics and physics, including an interest in the mathematical modelling and quantitative analysis of fluid mechanics, elastic bodies, heat transfer and so on.
- The combination of applied mathematics and engineering disciplines, advancing the application of mathematics to practical engineering problems and solving mathematical challenges in engineering.
Programme Structure and Funding
This programme is a full-time PhD programme with a duration of 4–5 years (48–60 months). Only 2 students are admitted.
Entry Requirements
Mathematics and Applied Mathematics, Statistics, Applied Mathematics, Physics, Engineering Mechanics, Fluid Mechanics, Materials Science, Computer Science, and engineering-related disciplines
- Academic background: a bachelor’s degree in mathematics, natural sciences, engineering, applied sciences, or social sciences with a strong mathematical background
- Grade requirements: GPA ≥ 3.0 (and an average grade point of ≥ 3.0 in all mathematics or quantitative-related courses)
- Language requirements: TOEFL: 90; or IELTS: 6.5 (with no sub-score below 6.0); Applicants who have obtained a degree in an English-taught country may apply for a language exemption
- References: 3 letters of recommendation
Application Materials
- CV;
- Undergraduate/master’s transcripts;
- English test score report;
- GRE score report (not mandatory);
- 3 letters of recommendation;
- Statement of purpose
Application Period
Spring entry application deadline: 15 October; Autumn entry application deadline: 15 December — first round; 1 May — final round
Application Process
From now until the end of February, applicants submit an English CV and relevant materials, and we will conduct a preliminary assessment. In March, those who pass the initial screening will be invited to interview with potential supervisors. In April, after passing the interview, applicants must formally submit their application materials through the official website. In May–June, shortlisted candidates will be interviewed by the college admissions committee. In July, admission offers will be issued. Note: the above are the timeline milestones for the final round of applications for autumn entry.
Tuition and Living Costs
Living Costs
Approximately USD 17,010 per year (depending on individual circumstances).
- Tuition: for the 2025–26 academic year, USD 14,951 per year (note: tuition rises slightly each year).
Career Prospects
The PhD programme in Applied Mathematics and Statistics at Stony Brook University, State University of New York, is known for its solid theoretical and interdisciplinary training. Its graduates are highly sought after in the job market and enjoy broad development prospects. Overall, their career paths are diverse and on an upward trend, with particularly strong demand in data-driven industries.
According to the US Bureau of Labor Statistics and related industry reports, professionals with doctoral degrees have a median annual salary significantly above average, typically above USD 100,000 to 150,000, with greater salary potential for senior professionals or those entering specific high-paying fields. In terms of career choices, PhD graduates mainly move into the following areas:
- Technology and industry: this is one of the main destinations.
Graduates can work in top technology companies (such as Google, Microsoft, Amazon and Meta) in highly technical roles such as machine learning, data science, algorithm research and quantitative analysis, solving complex problems such as recommendation systems, computer vision and natural language processing.
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Finance and consulting: in investment banks, hedge funds, private equity and fintech companies, PhDs leverage their modelling and statistical strengths in quantitative trading, risk modelling, financial derivatives pricing and actuarial analysis, serving as core intellectual support for financial innovation.
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Academia and high-end research institutions: some graduates enter universities or research-oriented colleges to teach and continue to advance the theoretical frontier. Many are also employed by government laboratories (such as national laboratories) and non-profit research institutions, conducting modelling and simulation research on national strategic topics involving defence, energy, climate and so on.
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Biomedicine and health data science: drawing on their deep statistical analysis capabilities, graduates play key roles in pharmaceutical companies, biotechnology firms and medical research centres, responsible for clinical trial design, genomics data analysis, epidemiological modelling and big data mining in healthcare.
