Department of Mathematics
Financial mathematics.
A pioneer in its field, the Financial Mathematics Program offers 15 months of accelerated, integrated coursework that explores the deep-rooted relationship that exists between theoretical and applied mathematics and the ever-evolving world of finance. Their mission is to equip students with a solid foundation in mathematics, and in doing so provide them with practical knowledge that they can successfully apply to complicated financial models. Financial Mathematics students become leaders in their field; program alumni have gone forth to find success at companies like JP Morgan, UBS, and Goldman Sachs. Read more
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The Mathematical and Computational Finance Program at Stanford University (“MCF”) is one of the oldest and most established programs of its kind in the world. Starting out in the late 1990’s as an interdisciplinary financial mathematics research group, at a time when “quants” started having a greater impact on finance in particular, the program formally admitted masters students starting in 1999. The current MCF program was relaunched under the auspices of the Institute for Computational and Mathematical Engineering in the Stanford School of Engineering in 2014 to better align with changes in industry and to broaden into areas of financial technology in particular. We are excited to remain at the cutting edge of innovation in finance while carrying on our long tradition of excellence.
The MCF Program is designed to have smaller cohorts of exceptional students with diverse interests and viewpoints, and prepare them for impactful roles in finance. We are characterized by our cutting edge curriculum marrying traditional financial mathematics and core fundamentals, with an innovative technical spirit unique to Stanford with preparation in software engineering, data science and machine learning as well as the hands-on practical coursework which is the hallmark skill-set for leaders in present day finance.
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- PhD in Mathematical Finance
The PhD in Mathematical Finance is for students seeking careers in research and academia. Doctoral candidates will have a strong affinity for quantitative reasoning and the ability to connect advanced mathematical theories with real-world phenomena. They will have an interest in the creation of complex models and financial instruments as well as a passion for in-depth analysis.
Learning Outcomes
The PhD curriculum has the following learning goals. Students will:
- Demonstrate advanced knowledge of literature, theory, and methods in their field.
- Be prepared to teach at the undergraduate, master’s, and/or doctoral level in a business school or mathematics department.
- Produce original research of quality appropriate for publication in scholarly journals.
After matriculation into the PhD program, a candidate for the degree must register for and satisfactorily complete a minimum of 16 graduate-level courses at Boston University. More courses may be needed, depending on departmental requirements.
PhD in Mathematical Finance Curriculum
The curriculum for the PhD in Mathematical Finance is tailored to each incoming student, based on their academic background. Students will begin the program with a full course load to build a solid foundation in not only math and finance but also the interplay between them in the financial world. As technology plays an increasingly larger role in financial models, computer programming is also a part of the core coursework.
Once a foundation has been established, students work toward a dissertation. Working closely with a faculty advisor in a mutual area of interest, students will embark on in-depth research. It is also expected that doctoral students will perform teaching assistant duties, which may include lectures to master’s-level classes.
Course Requirements
The minimum course requirement is 16 courses (between 48 and 64 units, depending on whether the courses are 3 or 4 units each). Students’ course choices must be approved by the Mathematical Finance Director prior to registration each term. The following is a typical program of courses.
- CAS EC 701 Microeconomic Theory
- CAS MA 711 Real Analysis
- CAS MA 779 Probability Theory I
- QST FE 918 Doctoral Seminar in Finance
- CAS EC 703 Advanced Microeconomic Theory
- CAS MA 776 Partial Differential Equations
- CAS MA 781 Probability Theory 2
- QST FE 920 Advanced Capital Market Theory
- CAS EC 702 Macroeconomic Theory
- CAS MA 783 Advanced Stochastic Processes
- QST MF 850 Advanced Computational Methods
- QST MF 922 Advanced Mathematical Finance
- CAS EC 704 Advanced Microeconomic Theory
- CAS MA 751 Statistical Machine Learning
- QST MF 810 FinTech Programming
- QST MF 921 Topics in Dynamic Asset Pricing
Additional Requirements
Qualifying examination.
Students must appear for a qualifying examination after completion of all coursework to demonstrate that they have:
- acquired advanced knowledge of literature and theory in their area of specialization;
- acquired advanced knowledge of research techniques; and
- developed adequate ability to craft a research proposal.
Guidelines for the examination are available from the departments. Students who do not pass either the written and/or oral comprehensive examination upon first try will be given a second opportunity to pass the exam. Should the student fail a second time, the student’s case will be reviewed by the Mathematical Finance Program Development Committee (MF PDC), which will determine if the student will be withdrawn from the PhD program. In addition, the PhD fellowship (if applicable) of any student who does not pass either the written and/or oral comprehensive examination after two attempts will be suspended the term after the exam was attempted.
Dissertation
Following successful completion of the qualifying examination, the student will develop a research proposal for the dissertation. The final phase of the doctoral program is the completion of an approved dissertation. The dissertation must be based on an original investigation that makes a substantive contribution to knowledge and demonstrates capacity for independent, scholarly research.
Doctoral candidates must register as continuing students for DS 999 Dissertation, a 2-unit course, for each subsequent regular term until all requirements for the degree have been completed. PhD students graduating in September are required to register for Dissertation in Summer Session II preceding graduation.
Academic Standards
Time limit for degree completion.
After matriculation into the PhD program, a candidate for the degree must meet certain milestones within specified time periods (as noted in the table below) and complete all degree requirements within six years of the date of first registration. Those who fail to meet the milestones within the specified time, or who do not complete all requirements within six years, will be reviewed by the PhD PDC and may be dismissed from the program. A Leave of Absence does not extend the six-year time limit for degree completion.
Milestone | Maximum Time Period |
---|---|
Complete all required courses (no Incompletes) | End of fall of 3rd year |
Successfully complete comprehensive examination | End of 3rd year |
Have a dissertation committee with at least three members, a committee chair, and a dissertation topic | End of fall of 4th year |
Have a defended dissertation proposal | End of 4th year |
Complete dissertation | End of 6th year |
Performance Review
The Mathematical Finance Program Development Committee will review the progress of each doctoral candidate. Students must maintain a 3.30 cumulative grade point average in all courses to remain in good academic standing. Students who are not in good academic standing will be allowed one term to correct their status. Prior to the start of the term, the student must submit a letter to the Faculty Director (who will forward it to the PDC) explaining why the student has fallen short of the CGPA requirement and how the student plans to correct the situation. Failure to increase the CGPA to acceptable levels may result in probation or withdrawal from the program, at the discretion of the PhD Program Development Committee (PDC).
Graduation Application
Students must submit a graduation application at least five months before the date they expect to complete degree requirements. It is the student’s responsibility to initiate the process for graduation. The application is available online and should be submitted through the Specialty Master’s & PhD Center website for graduation in January, May, or August.
If graduation must be postponed beyond the term for which the application is submitted, students should contact the Specialty Master’s & PhD Center to defer the date. If students wish to postpone their graduation date past the six-year time limit for completion, they must formally petition the PhD Program Development Committee (PDC) for an extension. The petition, which must include the reason(s) for the extension as well as a detailed timetable for completion, is subject to departmental and PDC approval.
PhD degree requirements are complete only when copies of the dissertation have been certified as meeting the standards of Questrom School of Business and have been accepted by Mugar Memorial Library.
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The field of finance covers the economics of claims on resources. Financial economists study the valuation of these claims, the markets in which they are traded, and their use by individuals, corporations, and the society at large.
At Stanford GSB, finance faculty and doctoral students study a wide spectrum of financial topics, including the pricing and valuation of assets, the behavior of financial markets, and the structure and financial decision-making of firms and financial intermediaries.
Investigation of issues arising in these areas is pursued both through the development of theoretical models and through the empirical testing of those models. The PhD Program is designed to give students a good understanding of the methods used in theoretical modeling and empirical testing.
Preparation and Qualifications
All students are required to have, or to obtain during their first year, mathematical skills at the level of one year of calculus and one course each in linear algebra and matrix theory, theory of probability, and statistical inference.
Students are expected to have familiarity with programming and data analysis using tools and software such as MATLAB, Stata, R, Python, or Julia, or to correct any deficiencies before enrolling at Stanford.
The PhD program in finance involves a great deal of very hard work, and there is keen competition for admission. For both these reasons, the faculty is selective in offering admission. Prospective applicants must have an aptitude for quantitative work and be at ease in handling formal models. A strong background in economics and college-level mathematics is desirable.
It is particularly important to realize that a PhD in finance is not a higher-level MBA, but an advanced, academically oriented degree in financial economics, with a reflective and analytical, rather than operational, viewpoint.
Faculty in Finance
Anat r. admati, juliane begenau, jonathan b. berk, michael blank, greg buchak, antonio coppola, darrell duffie, steven grenadier, benjamin hébert, arvind krishnamurthy, hanno lustig, matteo maggiori, paul pfleiderer, joshua d. rauh, claudia robles-garcia, ilya a. strebulaev, vikrant vig, jeffrey zwiebel, emeriti faculty, robert l. joss, george g.c. parker, myron s. scholes, william f. sharpe, kenneth j. singleton, james c. van horne, recent publications in finance, dollar safety and the global financial cycle, monetary tightening and u.s. bank fragility in 2023: mark-to-market losses and uninsured depositor runs, trading stocks builds financial confidence and compresses the gender gap, recent insights by stanford business, a “grumpy economist” weighs in on inflation’s causes — and its cures, the surprising economic upside to money in u.s. politics, your summer 2024 podcast playlist.
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Wharton’s PhD program in Finance provides students with a solid foundation in the theoretical and empirical tools of modern finance, drawing heavily on the discipline of economics.
The department prepares students for careers in research and teaching at the world’s leading academic institutions, focusing on Asset Pricing and Portfolio Management, Corporate Finance, International Finance, Financial Institutions and Macroeconomics.
Wharton’s Finance faculty, widely recognized as the finest in the world, has been at the forefront of several areas of research. For example, members of the faculty have led modern innovations in theories of portfolio choice and savings behavior, which have significantly impacted the asset pricing techniques used by researchers, practitioners, and policymakers. Another example is the contribution by faculty members to the analysis of financial institutions and markets, which is fundamental to our understanding of the trade-offs between economic systems and their implications for financial fragility and crises.
Faculty research, both empirical and theoretical, includes such areas as:
- Structure of financial markets
- Formation and behavior of financial asset prices
- Banking and monetary systems
- Corporate control and capital structure
- Saving and capital formation
- International financial markets
Candidates with undergraduate training in economics, mathematics, engineering, statistics, and other quantitative disciplines have an ideal background for doctoral studies in this field.
Effective 2023, The Wharton Finance PhD Program is now STEM certified.
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- Mathematical and Computational Finance @ Oxford
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DPhil (PhD) studies in Mathematical Finance @ Oxford
The Mathematical and Computational Finance Group (MCFG) at Oxford is one of the largest and most dynamic research environments in mathematical finance in the world.
We combine core mathematical expertise with interdisciplinary approach. We foster lively interactions between researchers coming from different backgrounds and a truly impressive seminar programme, all this within one of the world's top universities, singular through its tradition and unique environment.
If you are passionate about mathematics and research and want to pursue a DPhil in Financial Mathematics, Oxford simply offers one of the best and most exciting places to do it!
Research Topic and Supervisor Allocation
We welcome students with their own particular ideas of research topic as well as students with a broad interest in the field of Mathematical Finance. You have an opportunity to tell us about your research passions, and indicate potential supervisors, in your application form. This will be followed up during the interview.
In light of this, if you are offered a place, an appropriate supervisor will be proposed prior to your arrival in Oxford. However, there can be some flexibility over this once you arrive. Keeping with the Oxford tradition, we offer our students independence and respect as early researchers, and always aim to match students with the most appropriate supervisors.
Outstanding students with a strong background in analysis, probability and data science are welcome to apply for our DPhil program. Each year we receive a large number of excellent applications. The selection process is extremely competitive and we can only admit a handful of candidates each year.
In order to apply for DPhil studies in Mathematical & Computational Finance, please indicate your interest in Mathematical and Computational Finance on your application form. Selected applicants will be invited for an interview -- either in person or by video call.
For general information on DPhil please consult our Doctor of Philosophy (DPhil) admissions pages .
For the CDT Mathematics of Random Systems please consult our the CDT website .
Or please contact @email .
Funding for DPhil students is available from a variety of sources. Please note that some funding opportunities have deadlines: it is advised to apply before the deadline in order to maximise your chances of receiving funding.
Funding is also available through the Centre for Doctoral Training in Mathematics of Random Systems . To apply for this program please How to Apply .
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DPhil Graduates
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Through intellectual rigor and experiential learning, this full-time, two-year MBA program develops leaders who make a difference in the world.
Earn your MBA and SM in engineering with this transformative two-year program.
A rigorous, hands-on program that prepares adaptive problem solvers for premier finance careers.
A 12-month program focused on applying the tools of modern data science, optimization and machine learning to solve real-world business problems.
Combine an international MBA with a deep dive into management science. A special opportunity for partner and affiliate schools only.
A doctoral program that produces outstanding scholars who are leading in their fields of research.
Bring a business perspective to your technical and quantitative expertise with a bachelor’s degree in management, business analytics, or finance.
Apply now and work for two to five years. We'll save you a seat in our MBA class when you're ready to come back to campus for your degree.
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A full-time MBA program for mid-career leaders eager to dedicate one year of discovery for a lifetime of impact.
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PhD Program in Finance
2023-24 curriculum outline.
The MIT Sloan Finance Group offers a doctoral program specialization in Finance for students interested in research careers in academic finance. The requirements of the program may be loosely divided into five categories: coursework, the Finance Seminar, the general examination, the research paper, and the dissertation. Attendance at the weekly Finance Seminar is mandatory in the second year and beyond and is encouraged in the first year. During the first two years, students are engaged primarily in coursework, taking both required and elective courses in preparation for their general examination at the end of the second year. Students are required to complete a research paper by the end of their fifth semester, present it in front of the faculty committee and receive a passing grade. After that, students are required to find a formal thesis advisor and form a thesis committee by the end of their eighth semester. The Thesis Committee should consist of at least one tenured faculty from the MIT Sloan Finance Group.
Required Courses
The following set of required courses is designed to furnish each student with a sound and well-rounded understanding of the theoretical and empirical foundations of finance, as well as the tools necessary to make original contributions in each of these areas. Finance PhD courses (15.470, 15.471, 15.472, 15.473, 15.474) in which the student does not receive a grade of B or higher must be retaken.
First Year - Summer
Math Camp begins on the second Monday in August.
First Year - Fall Semester
14.121/14.122 Micro Theory I/II
14.451/14.452 Macro Theory I/II ( strongly recommended)
14.380/14.381 — Statistics/Applied Econometrics
15.470 — Asset Pricing
First Year - Spring Semester
14.123/14.124 Micro Theory III/IV
14.453/14.454 Macro Theory III/IV (strongly recommended)
14.382 – Econometrics
15.471 – Corporate Finance
Second Year - Fall Semester
15.472 — Advanced Asset Pricing
14.384 — Time-Series Analysis or 14.385 — Nonlinear Econometric Analysis (Enrolled students receive a one-semester waiver from attending the Finance Seminar due to a scheduling conflict)
15.475 — Current Research in Financial Economics
Second Year - Spring Semester
15.473 — Advanced Corporate Finance
15.474 — Current Topics in Finance (strongly encouraged to take multiple times)
15.475 — Current Research in Financial Economics
Recommended Elective Courses
Beyond these required courses, students are expected to enroll in elective courses determined by their primary area of interest. There are two informal “tracks” in Financial Economics: Corporate Finance and Asset Pricing. Recommended electives are designed to deepen the student's grasp of material that will be central to the writing of his/her dissertation. Students also have the opportunity to take courses at Harvard University. There is no formal requirement to select one track or another, and students are free to take any of the electives.
- US Rankings
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2024 QuantNet Ranking of Best Financial Engineering Programs
The QuantNet ranking of Financial Engineering, Mathematical, and Quantitative Finance master's programs in the US offers detailed insights into placement and admission statistics from the nation's top programs. It serves as the ultimate guide for prospective applicants, helping them choose and enroll in the best master’s programs in quantitative finance.
Baruch College
Princeton university, carnegie mellon university, university of california, berkeley, columbia university, university of chicago, cornell university, new york university, massachusetts institute of technology.
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NYU Tandon School of Engineering
Georgia institute of technology, north carolina state university, university of california, los angeles, johns hopkins university, university of washington, rutgers university, university of illinois urbana champaign, stevens institute of technology, university of minnesota, boston university, fordham university, uc san diego.
Rank | Program | Total Score | Peer Score | % Employed at Graduation | % Employed at 3 months | Salary | Cohort Size | Tuition |
---|---|---|---|---|---|---|---|---|
1 | 4.93 star(s) | 100 | 4.3 | 100% | 100% | $220,500 | 24 FT, 4 PT | $42,395 |
2 | 4.86 star(s) | 97 | 4 | 100% | 100% | $240,611 | 37 FT | $125,720 |
3 | 4.64 star(s) | 95 | 4.3 | 92% | 97% | $160,336 | 95 FT | $97,061 |
4 | 4.45 star(s) | 91 | 3.9 | 84% | 96% | $173,758 | 76 FT, 11 PT | $80,486 |
5 | 3.30 star(s) | 88 | 3.6 | 66% | 100% | $154,175 | 106 FT | $88,632 |
6 | 4.74 star(s) | 85 | 3.6 | 90% | 98% | $143,216 | 127 FT, 6 PT | $90,013 |
7 | 4.71 star(s) | 83 | 3.4 | 75% | 95% | $144,433 | 53 FT | $97,806 |
7 | 4.33 star(s) | 83 | 3.7 | 80% | 97% | $142,252 | 24 FT, 4 PT | $75,000 |
9 | 4.00 star(s) | 82 | 3.3 | 76% | 88% | $123,894 | 105 FT, 3 PT | $94,850 |
9 | 3.77 star(s) | 82 | 3.1 | 82% | 98% | $140,123 | 127 FT | $121,009 |
11 | 3.43 star(s) | 77 | 3.1 | 71% | 91% | $114,967 | 146 FT, 1 PT | $78,433 |
12 | 3.78 star(s) | 76 | 2.9 | 91% | 97% | $131,490 | 71 FT | $60,228 |
12 | 4.46 star(s) | 76 | 2.6 | 89% | 100% | $116,882 | 33 FT | $63,023 |
12 | 4.43 star(s) | 76 | 3.4 | 89% | 94% | $125,727 | 94 FT | $89,539 |
15 | 4.56 star(s) | 66 | 2.4 | 61% | 100% | $110,874 | 49 FT | $95,203 |
15 | 4.95 star(s) | 66 | 2.8 | 74% | 100% | $105,261 | 52 FT | $47,570 |
17 | 4.08 star(s) | 62 | 2.7 | 57% | 89% | $106,520 | 55 FT | $76,224 |
18 | 4.51 star(s) | 58 | 2.7 | 54% | 92% | $106,150 | 23 FT | $78,837 |
19 | 4.38 star(s) | 57 | 2.4 | 45% | 98% | $114,483 | 16 FT, 4 PT | $54,332 |
20 | 4.71 star(s) | 55 | 2.2 | 82% | 91% | $122,040 | 18 FT, 1 PT | $49,420 |
21 | 3.30 star(s) | 49 | 2.7 | 54% | 78% | $109,098 | 106 FT | $97,226 |
21 | 5.00 star(s) | 49 | 2.2 | 46% | 69% | $103,640 | 23 FT | $89,309 |
21 | 5.00 star(s) | 49 | 2.1 | 24% | 57% | $81,935 | 146 FT | $76,128 |
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Financial Mathematics
Graduate programs.
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Department of statistics and applied probability - uc santa barbara, financial mathematics and statistics, fms overview.
The department offers an optional emphasis in Financial Mathematics and Statistics (FMS) for students pursuing a Ph.D. The FMS emphasis allows students to specialize in the emerging field of financial mathematics and statistics. The Center for Financial and Actuarial Research provides students a great opportunity to work with a thriving group of researchers taking a cross-disciplinary approach to financial mathematics.
Students interested in adding the FMS Emphasis must apply before their preliminary oral qualifying exam and subsequent advancement to candidacy takes place. Please see the Graduate Program Advisor with questions regarding requirements or application procedures.
FMS Resources
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FMS Application
The Center for Financial Mathematics and Actuarial Research
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Financial Mathematics MSE
Our Program At Johns Hopkins, Financial Mathematics continues a rich engineering tradition whereby the strengths of the faculty in research, education, and leadership are applied to expand knowledge and apply new knowledge for the benefit of humanity by addressing the complex problems of modern society. Understanding and navigating today’s rapidly evolving, world-wide economic and financial landscape presents one of society’s most challenging current problems.
The Field of Financial Mathematics Financial Mathematics (commonly described using an array of roughly synonymous alternative titles including Financial Engineering, Computational Finance, Mathematical Finance, and Quantitative Finance) is an engineering discipline fundamentally enabled by the intellectual pursuits spanned by the faculty of Applied Mathematics and Statistics (AMS): probability, statistics, optimization, partial differential equations and scientific computing.
The unifying premise for Financial Mathematics is more than just a collection of techniques applied to a common problem area. Rather, it quantifies and enables much of the modern interplay in global markets among companies, investors, and financial agents; constrained or constructed by the actions of central banks, regulators and governments. Global financial agents, which include broker-dealers on Wall Street, in London, Hong Kong and elsewhere, create and package (or repackage) capital products and services into the instruments that are so vital to the course of world-wide capital allocation, investment, and risk transfer. None of this could occur today without the sophisticated approaches enabled by financial mathematics which have evolved over the past 25 years.
A Culture of Collaboration Because of a strong university-wide commitment to collaboration, we benefit from scholarship from across the university, and particularly in the areas of business, finance, economics, computing, and management in the Carey Business School and from the Department of Economics in the Krieger School of Arts and Sciences, as well as from the other departments and programs in the Whiting School of Engineering.
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Financial Mathematics Master's Program Online
The online Financial Mathematics degree programs offered by the Johns Hopkins Engineering for Professional sharpens and complements your quantitative and managerial skills with engineering-driven principles that power our global economy.
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Financial Mathematics Programs Overview
In the graduate Financial Mathematics program at Johns Hopkins Engineering for Professionals, you will examine the engineering-driven principles that power our global economy in courses that focus on developing advanced quantitative and managerial skills in finance. Gain expansive knowledge, tools, and techniques to incorporate into your work immediately and in the foreseeable future.
The online financial mathematics degree programs offer you the opportunity to:
- Study relevant scenarios in subjects that translate to execution in the real-world, including financial derivatives, risk management, and quantitative portfolio theory.
- Learn from faculty who are top performers and experts with practical experience at world-renowned organizations, including Goldman Sachs, Bank of America, and top hedge funds.
- Lead with confidence with financial, technical, and managerial skills.
- Learn on your terms and select a flexible course schedule in a format that works best for you.
Master’s Degrees & Certificates
- Master of Science in Financial Mathematics
- Graduate Certificate in Financial Risk Management
- Graduate Certificate in Quantitative Portfolio Management
- Graduate Certificate in Securitization
We offer four program options for Financial Mathematics. Earn a Master of Science in Financial Mathematics online or earn one of our three financial engineering certificates online—Graduate Certificate in Financial Risk Management, Graduate Certificate in Quantitative Portfolio Management or Graduate Certificate in Securitization.
Financial Mathematics Courses
Get details about course requirements, prerequisites, and electives offered within for the master’s degree in financial mathematics and certificate programs. All courses are taught by subject-matter experts who are executing the technologies and techniques they teach. For exact dates, times, locations, fees, and instructors, please refer to the course schedule published each term.
Program Contacts
David audley.
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Meghan Stewart
Tuition and fees.
Did you know that 78 percent of our enrolled students’ tuition is covered by employer contribution programs? Find out more about the cost of tuition for prerequisite and program courses and the Dean’s Fellowship.
Why Hopkins?
Make your ambitions a reality by earning your master’s in financial mathematics online and on your own schedule.
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Career-Advancing Knowledge - Coursework incorporates industry-specific knowledge that you can use from day one. As a graduate, you will be prepared to advance your career, cross over into other engineering fields, take on leadership roles, and increase your income-earning potential. Learn More
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Learn on Your Terms - Take courses completely online, on-site, or a hybrid of online and on-site. We also offer virtual live—a synchronous, live instruction option that allows you to take a course at a scheduled time, with your classmates, but in your own space.
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Network and Connect - Your knowledge is stronger with a network. In the financial mathematics program, make career-advancing connections with accomplished scientists and engineers who represent a variety of disciplines across many industries. Learn More
“ I enjoyed the flexibility of attending part-time, the personableness of the instructors in the program, and the content of the courses I took. ”
Financial Mathematics FAQs
What can i do with a master’s degree in financial mathematics.
Due to the wide-ranging nature of financial mathematics, graduates have worked in places ranging from insurance companies to the government to analyzing data for stockbrokers. Job titles include Quantitative Analyst, Data Scientist, Quantitative Researcher, and more.
Can I get a graduate financial engineering certificate online?
Yes! Both the master’s and graduate certificate programs are designed specifically to be completed 100% online.
I don't have an engineering background, can I still apply to this program?
Your prior education must include an undergraduate or graduate degree in a quantitative discipline (e.g., mathematics, engineering, or the sciences) with a minimum of two years of relevant full-time work experience in finance or a related field. If you are admitted under provisional status, prerequisite course requirements must be completed at a regionally accredited university/college, and you must have received a B– grade or higher.
Academic Calendar
Find out when registration opens, classes start, transcript deadlines and more. Applications are accepted year-round, so you can apply any time.
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Best Financial Mathematics colleges in the U.S. 2024
Best financial mathematics colleges in the u.s. for 2024.
![best phd in financial mathematics best phd in financial mathematics](https://media.universities.com/cache/school_xxl/images/school/2142442-mit.jpeg)
Massachusetts Institute of Technology offers 2 Financial Mathematics degree programs. It's a large, private not-for-profit, four-year university in a midsize city. In 2022, 144 Financial Mathematics students graduated with students earning 133 Master's degrees, and 11 Bachelor's degrees.
![best phd in financial mathematics best phd in financial mathematics](https://media.universities.com/cache/school_xxl/images/school/1898072-university-of-chicago.jpeg)
University of Chicago offers 1 Financial Mathematics degree programs. It's a large, private not-for-profit, four-year university in a large city. In 2022, 144 Financial Mathematics students graduated with students earning 144 Master's degrees.
![best phd in financial mathematics best phd in financial mathematics](https://www.universities.com/build/images/woman-on-laptop-in-library.d28ae37b.png)
Johns Hopkins University offers 4 Financial Mathematics degree programs. It's a very large, private not-for-profit, four-year university in a large city. In 2022, 12 Financial Mathematics students graduated with students earning 12 Master's degrees.
![best phd in financial mathematics best phd in financial mathematics](https://media.universities.com/cache/school_xxl/images/school/2082346-vanderbilt.jpeg)
Vanderbilt University offers 1 Financial Mathematics degree programs. It's a large, private not-for-profit, four-year university in a large city. In 2022, 142 Financial Mathematics students graduated with students earning 142 Master's degrees.
![best phd in financial mathematics best phd in financial mathematics](https://media.universities.com/cache/school_xxl/images/school/1897921-university-of-california-berkeley.jpeg)
University of California-Berkeley offers 1 Financial Mathematics degree programs. It's a very large, public, four-year university in a midsize city. In 2022, 79 Financial Mathematics students graduated with students earning 79 Master's degrees.
![best phd in financial mathematics best phd in financial mathematics](https://media.universities.com/cache/school_logo/images/school/university-of-notre-dame-logo-30112.jpeg)
University of Notre Dame offers 1 Financial Mathematics degree programs. It's a large, private not-for-profit, four-year university in a large suburb. In 2022, 101 Financial Mathematics students graduated with students earning 101 Master's degrees.
![best phd in financial mathematics best phd in financial mathematics](https://media.universities.com/cache/school_logo/images/school/boston-college-logo-13918.jpeg)
Boston College offers 2 Financial Mathematics degree programs. It's a large, private not-for-profit, four-year university in a small city. In 2022, 117 Financial Mathematics students graduated with students earning 117 Master's degrees.
![best phd in financial mathematics best phd in financial mathematics](https://media.universities.com/cache/school_xxl/images/school/34-2623267-usc.jpeg)
University of Southern California offers 2 Financial Mathematics degree programs. It's a very large, private not-for-profit, four-year university in a large city. In 2022, 190 Financial Mathematics students graduated with students earning 119 Master's degrees, and 71 Bachelor's degrees.
![best phd in financial mathematics best phd in financial mathematics](https://media.universities.com/cache/school_xxl/images/school/2142515-carnegie-mellon.jpeg)
Carnegie Mellon University offers 3 Financial Mathematics degree programs. It's a large, private not-for-profit, four-year university in a large city. In 2022, 9 Financial Mathematics students graduated with students earning 9 Bachelor's degrees.
![best phd in financial mathematics best phd in financial mathematics](https://media.universities.com/cache/school_xxl/images/school/1992299-uc-la.jpeg)
University of California-Los Angeles offers 1 Financial Mathematics degree programs. It's a very large, public, four-year university in a large city. In 2022, 61 Financial Mathematics students graduated with students earning 61 Bachelor's degrees.
Find local colleges with Financial Mathematics majors in the U.S.
List of all financial mathematics colleges in the u.s..
School | Average Tuition | Student Teacher Ratio | Enrolled Students | |
---|---|---|---|---|
Cambridge, MA | 5/5 | 8 : 1 | 11,858 | |
Chicago, IL | 5/5 | 11 : 1 | 18,339 | |
Baltimore, MD | 5/5 | 22 : 1 | 31,275 | |
Nashville, TN | 5/5 | 11 : 1 | 13,710 | |
Berkeley, CA | 3/5 | 24 : 1 | 45,307 |
2024 Best Financial Mathematics Schools
Featured financial mathematics programs, choosing a great financial mathematics school, financial mathematics rankings by degree level, best schools for financial mathematics in the united states, 10 top schools in financial math.
There were approximately 144 financial mathematics students who graduated with this degree at UChicago in the most recent year we have data available.
There were about 12 financial mathematics students who graduated with this degree at Johns Hopkins in the most recent year we have data available.
Put mathematical concepts to work to solve today's most complex real-world problems by studying applied mathematics with this specialized online bachelor's from Southern New Hampshire University.
Related Programs
There were about 360 financial mathematics students who graduated with this degree at WUSTL in the most recent data year.
There were approximately 144 financial mathematics students who graduated with this degree at MIT in the most recent data year.
There were about 9 financial mathematics students who graduated with this degree at Carnegie Mellon in the most recent year we have data available.
There were approximately 101 financial mathematics students who graduated with this degree at Notre Dame in the most recent year we have data available.
There were approximately 190 financial mathematics students who graduated with this degree at USC in the most recent data year.
There were approximately 142 financial mathematics students who graduated with this degree at Vanderbilt in the most recent year we have data available.
There were roughly 61 financial mathematics students who graduated with this degree at UCLA in the most recent data year.
There were approximately 46 financial mathematics students who graduated with this degree at NYU in the most recent year we have data available.
Additional Noteworthy Schools
Rank | College | Location |
---|---|---|
11 | Dallas, TX | |
12 | Coral Gables, FL | |
13 | Columbus, OH | |
14 | College Park, MD | |
15 | Chestnut Hill, MA |
Financial Mathematics by Region
Region |
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Other Rankings
Bachelor's degrees in financial math, doctor's degrees in financial math, master's degrees in financial math, financial mathematics related rankings by major, majors similar to financial math.
Related Major | Annual Graduates |
---|---|
4,544 | |
951 | |
416 | |
311 | |
26 |
Notes and References
Popular reports, compare your school options.
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Mathematics (PHD) – Financial Mathematics Track
Program at a glance.
- In State Tuition
- Out of State Tuition
Learn more about the cost to attend UCF.
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The Financial Mathematics track in the Mathematics PhD program is designed to prepare students for research and leadership positions in industry, government, non-governmental organizations, and academia requiring employment of financial mathematics.
The Mathematics PhD program consists of 75 credit hours of course work beyond the bachelor's degree. This includes a minimum of 45 hours of formal course work. Of the 45 hours, 33 hours are from required courses and 12 are from elective courses. In addition to formal coursework, 15 elective hours can come from independent study, directed research, and internship. Lastly, 15 credit hours of dissertation research (7980) are required.
Master en route is permitted and encouraged.
Total Credit Hours Required: 75 Credit Hours Minimum beyond the Bachelor's Degree
Application Deadlines
- International
Ready to get started?
University of central florida colleges.
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Enter your information below to receive more information about the Mathematics (PHD) – Financial Mathematics Track program offered at UCF.
Track Prerequisites
Bachelor's degree in related field.
Students entering the graduate program with regular status are assumed to have a working knowledge of undergraduate calculus, differential equations, linear algebra (or matrix theory), boundary value problems, statistics, computer programming, and maturity in the language of advanced calculus (at the level of MAA 4226) and linear algebra (at the level of MAS3106).
Degree Requirements
Required courses.
- All students are required to complete the following courses with grade of "B" or better.
- MAA5237 - Mathematical Analysis (3)
- MAS5145 - Advanced Linear Algebra and Matrix Theory (3)
- MAP5641 - Financial Mathematics I (3)
- MAP6642 - Financial Mathematics II (3)
- MAP5612 - Computational Methods for Financial Mathematics I (3)
- MAP6616 - Computational Methods for Financial Mathematics II (3)
- MAP6646 - Risk Management for Financial Mathematics (3)
- MAP5606 - Differential Equations for Financial Mathematics (3)
- MAP5931 - Proseminar for Financial Mathematics (1)
- MAP5933 - Seminar in Financial Mathematics (2)
- MAP6195 - Mathematical Foundations for Massive Data Modeling and Analysis (3)
- MAP6197 - Mathematical Introduction to Deep Learning (3)
- MAP6207 - Optimization Theory (3)
- STA6857 - Applied Time Series Analysis (3)
- ECO6281 - Financial Economics I: Asset Prices, Risk, and Information (3)
- ECO6282 - Financial Economics II: Continuous-Time Models (3)
- Students may substitute some of the core courses with the approval of the graduate program director.
Elective Courses
- Earn at least 27 credits from the following types of courses: Elective courses require the approval of the adviser and the graduate program director. Except those listed as core courses, up to 9 credit hours of elective courses may be taken outside the department. At least one-half of the program courses must be taken at the 6000 level. At most 15 credit hours on independent study and directed research and internship can be used as Elective Courses. At least 12 hours of elective course work must be formal course work. Electives are chosen in consultation with the student's advisory committee and may be chosen from the suggested options: Discrete Mathematics, General Applied Mathematics, Mathematical Finance, Pure Mathematics, Data Science, and Mathematical Statistics. A list of elective course options can be obtained from the graduate program director. Courses that are taken outside the Mathematics department must be approved by the graduate program director. Internship is strongly encouraged to take, however it is not mandatory. The following courses (if not used as core courses) are encouraged to take as elective courses. • MAP6195 - Mathematical Foundations for Massive Data Modeling and Analysis (3) • MAP 6197: Mathematical Introduction to Deep Learning (3) • MAP6207 - Optimization Theory (3) • STA6857 - Applied Time Series Analysis (3) • ECO6281 Financial Economics I—Asset Prices, Risk, and Information (3) • ECO6282 Financial Economics II—Continuous-Time Models (3) • MAA 6238: Measure and Probability I (3) • MAA 6245: Measure and Probability II (3) • MAP 6218: Stochastic Calculus (3) • MAP 6111: Mathematical Statistics (3) • MAP 6469: Bayesian Analysis and Approximation Theory (3) • MAA 7239: Asymptotic Methods in Mathematical Statistics (3) • MAD5205 - Graph Theory I (3) • MAD 6309: Graph Theory II (3) • MAA6306 - Real Analysis (3) • MAA6505 – Functional Analysis (3)
Dissertation
- Earn at least 15 credits from the following types of courses: MAP 7980 - Dissertation Research 15 Credit Hours (minimum) After passing the candidacy examination and meeting the other requirements that are required for admission to candidacy, the student can register for Doctoral Dissertation (MAP 7980). A minimum of 15 Doctoral Dissertation credit hours are required for the degree.
Examinations
Qualifying examination.
- The qualifying/comprehensive examination is based on the core course work. To continue in the PhD program, students must pass the examination at the PhD level. Two attempts are permitted. The examination will be administered twice a year: one in the Fall semester and the other in the Spring semester. To take the examination, students must have earned a "B" or better in each core course, must have a minimum grade point average of 3.0 (out of 4.0) in the program, or must obtain permission from the graduate program director. Students will normally take the examination after taking courses MAA 5237 and MAS 5145. Students are expected to have passed the examination by the end of the second year of study, unless a written request for a postponement has been approved by the Graduate Committee at least two months before the examination date. The student must pass the Qualifying Examination in at most two attempts. It is strongly recommended that the student select a dissertation adviser by the completion of 18 credit hours of course work, and it is strongly recommended that the student works with the dissertation adviser to form a dissertation committee within two semesters of passing the Qualifying Examination.
Candidacy Examination
- The Candidacy Examination consists of a written examination based on the materials from two selected two-semester sequence courses taken by the students. A committee formed or selected by the Graduate Committee or the graduate program director is responsible for preparing and grading the written examinations. Each sequence that is selected for the candidacy examination must be approved by the dissertation adviser, the dissertation committee, and the graduate program director. Students in the Financial Mathematics Track will ordinarily select one of the sequences for their candidacy examination to be MAP 5641/MAP6642 Financial Mathematics I and II, and MAP5612/MAP6616 Computational Methods for Financial Mathematics I and II. The student can apply for the candidacy exam waiver on one sequence and should discuss with the program director for the procedure and the requirement. The Candidacy Examination can be attempted after passing the qualifying examination. The Candidacy Examination must be completed within one and half years after passing the qualifying examination. A student must successfully pass the Candidacy Examination within at most two attempts.
Admission to Candidacy
- The following are required to be admitted to candidacy and enroll in dissertation hours: Completion of all course work, except for dissertation hours. Successful completion of the candidacy examination. The dissertation advisory committee is formed, consisting of approved graduate faculty and graduate faculty scholars. Submittal of an approved program of study.
Dissertation Proposal Examination
- After passing the candidacy examination, the student will prepare a dissertation proposal and orally present it to the dissertation advisory committee for approval. The proposal will include a description of the research performed to date and an agenda for the research planned to be completed for the dissertation. In addition to standards of correctness, indicating a suitable level of mastery of the material of the area of the dissertation, and suitability of the proposed dissertation topic, the presentation must meet current standards for professional presentations within the discipline of mathematics. For the successful completion of the Dissertation Proposal Examination, the presentation must be judged as passing the requirements for the examination by the majority of the dissertation committee. This exam must be passed within 18 months of passing the candidacy examination and not later than the end of the sixth year of graduate study. A candidate must pass this examination within at most two attempts.
Dissertation Defense
- Upon completion of a student's research, the student's committee schedules an oral defense of the dissertation. Most students complete the program within five years after obtaining their bachelor's degree. Students are expected to complete the dissertation in no more than seven years from the date of admission to the program.
Independent Learning
- The required 15 credit hours of dissertation will provide ample opportunities for students to gain the independent learning experience through studying published research papers and deriving, on their own, new and meaningful research results.
Grand Total Credits: 75
Application requirements, financial information.
Graduate students may receive financial assistance through fellowships, assistantships, tuition support, or loans. For more information, see the College of Graduate Studies Funding website, which describes the types of financial assistance available at UCF and provides general guidance in planning your graduate finances. The Financial Information section of the Graduate Catalog is another key resource.
Fellowship Information
Fellowships are awarded based on academic merit to highly qualified students. They are paid to students through the Office of Student Financial Assistance, based on instructions provided by the College of Graduate Studies. Fellowships are given to support a student's graduate study and do not have a work obligation. For more information, see UCF Graduate Fellowships, which includes descriptions of university fellowships and what you should do to be considered for a fellowship.
The department offers over 20 Graduate Teaching Assistantships every year on a competitive basis. A few Graduate Research Assistantships are also available for qualified students.
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Master of Philosophy in Mathematics Doctor of Philosophy in Mathematics
MPhil(MATH) PhD(MATH)
Both full- and part-time
Full-time: 2 years Part-time: 4 years
Full-time: 3 years (with a relevant research master’s degree), 4 years (without a relevant research master’s degree) Part-time: 6 years
Department of Mathematics
PG Programs Coordinator: Prof Tianling JIN, Associate Professor of Mathematics
https://www.math.hkust.edu.hk/pg/
The Master of Philosophy (MPhil) Program seeks to strengthen students’ general background in mathematics and mathematical sciences, and to expose students to the environment and scope of mathematical research. A candidate for an MPhil degree is expected to demonstrate knowledge in the discipline and to synthesize and create new knowledge, making a contribution to the field. It can be a terminal degree or a preliminary degree leading to the PhD.
The Doctor of Philosophy (PhD) Program aims to prepare students to become research scholars in an academic or industrial environment and enable students to do independent and original research. It provides a broad background in mathematics and mathematical sciences. Students can choose to focus their research in one of the three areas: Pure Mathematics, Applied Mathematics, and Probability and Statistics. A candidate for a PhD degree is expected to demonstrate mastery of knowledge in the chosen discipline and to synthesize and create new knowledge, making an original and substantial contribution to the discipline.
On successful completion of the MPhil program, graduates will be able to:
- Conduct research in mathematics;
- Demonstrate knowledge in the chosen discipline of mathematics;
- Be able to synthesize and create new knowledge and to making contributions to the discipline of mathematics; and
- Demonstrate communication skills in presenting reporting findings in mathematics.
On successful completion of the PhD program, graduates will be able to:
- Be able to conduct independent and original research in mathematics;
- Demonstrate mastery of knowledge in the chosen discipline of mathematics;
- Be able to synthesize and create new knowledge and to make original and substantial contributions to the discipline of mathematics;
- Demonstrate a broad knowledge in mathematics and mathematical sciences; and
- Demonstrate effective communication skills in presenting and publishing findings in mathematics.
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The programs are offered by the Department of Mathematics with the following research foci and state-of-the-art facilities, strengthening students’ knowledge in mathematics and training them to carry out original research independently and innovatively.
Research Foci
Algebra and Number Theory
Representation theory of reductive groups, quantum groups, infinite dimensional Lie groups and Lie algebras and applications to mathematical physics and number theory.
Geometry and Topology
Algebraic geometry, differential geometry, low dimensional topology, equivariant topology, combinatorics and combinatorial topology, and geometrical structures in mathematical physics.
Analysis and Differential Equations
Complex analysis, exponential asymptotics, functional analysis, harmonic analysis, wavelets analysis, nonlinear equations and dynamical systems, integrable systems, fluid dynamics, and inverse problems.
Applied and Computational Mathematics
Modeling and simulation in fluid dynamics and materials science, computational fluid dynamics, multiscale modeling, kinetic theory, atomistic simulations, image processing, computational harmonic analysis, inverse problems and wave propagation, graph theory, optimization, evolutionary genetics, environmental science, numerical weather prediction, ocean and coastal modeling, numerical analysis, parallel algorithms, and numerical software.
Financial Mathematics
Asset allocation/management, derivative modeling, pricing and hedging and division or firm-wise risk management are traditional research areas. The recent trend of financial mathematics research is data driven, adopting methodologies of big data and machine learning.
Probability and Statistics
Time series and dependent data, resampling methodology, stochastic processes and stochastic analysis, and survival analysis, random matrix, statistical physics and high-dimensional statistics.
Data Science
Financial statistics, econometrics, statistical machine learning, statistical genetics and genomics, computational biology and bioinformatics, error in variables model, generalized linear models; biological and medical statistics, topological and geometric methods in data analysis.; mathematical data analysis, in terms of accuracy, running time, memory efficiency, scalability, or other computational measures.
The Department enjoys a range of up-to-date computing facilities. Besides a laboratory with 40 high-end desktop PCs, there is also a High Performance Computing laboratory equipped with 200 powerful CPU- & GPU-based computer servers having 250 TFLOPS processing power and 1.5PB storage capacity. Moreover, the NVIDIA DGX SuperPOD Supercomputer in the Hong Kong campus and the Tianhe2 Supercomputer in the Guangzhou Fok Ying Tung Research Institute are also available.
Minimum Credit Requirement
MPhil: 24 credits PhD: 36 credits
Credit Transfer
PhD students who have obtained an MSc or MPhil degree from other institutions may be granted credit transfer of up to 18 credits, subject to departmental approval.
Required Courses
MPhil: 24 credits in mathematics or related fields, normally including at least 18 credits of mathematics courses at postgraduate level. PhD: 36 credits in mathematics or related fields, including at least 24 credits of mathematics courses at postgraduate level. PhD students can choose to focus their research in one of the three areas:
Pure Mathematics;
Applied Mathematics; and
Probability and Statistics.
Students with a first degree in an area other than mathematics may be required to take additional courses.
Graduate Teaching Assistant Training
All full-time RPg students are required to complete PDEV 6800. The course is composed of a 10-hour training offered by the Center for Education Innovation (CEI), and session(s) of instructional delivery to be assigned by the respective departments. Upon satisfactory completion of the training conducted by CEI, MPhil students are required to give at least one 30-minute session of instructional delivery in front of a group of students for one term. PhD students are required to give at least one such session each in two different terms. The instructional delivery will be formally assessed.
Professional Development Course Requirement
Students are required to complete PDEV 6770. The 1 credit earned from PDEV 6770 cannot be counted toward the credit requirements. PhD students who are HKUST MPhil graduates and have completed PDEV 6770 or other professional development courses offered by the University before may be exempted from taking PDEV 6770, subject to prior approval of the School.
Students are required to complete MATH 6771. The 1 credit earned from MATH 6771 cannot be counted toward the credit requirements. PhD students who are HKUST MPhil graduates in Mathematics and have completed MATH 6771 before may be exempted from taking MATH 6771, subject to prior approval of the Department Head or Department PG Coordinator.
English Language Requirement
Full-time RPg students are required to take an English Language Proficiency Assessment (ELPA) Speaking Test administered by the Center for Language Education before the start of their first term of study. Students whose ELPA Speaking Test score is below Level 4, or who failed to take the test in their first term of study, are required to take LANG 5000 until they pass the course by attaining at least Level 4 in the ELPA Speaking Test before graduation. The 1 credit earned from LANG 5000 cannot be counted toward the credit requirements.
Students are required to complete LANG 5005 and advised to complete it in the first year of study. The 1 credit earned from LANG 5005 cannot be counted toward the program credit requirements. PhD students who are HKUST MPhil graduates may be considered for exemption from this course, subject to the approval of their department.
Postgraduate Seminar
Full-time students are required to complete MATH 6900 in their first four regular terms of study. The maximum number of credits to be earned from this course is 4.
PhD Qualifying Examination
PhD students are required to pass a qualifying examination. Pure Mathematics To become PhD candidates, students must first pass a written qualifying examination (normally at the end of the first year of study) on two of the three subject areas: analysis, algebra, and geometry. At a later date (normally no later than the end of the second year of study) an oral examination on a major area excluding the two areas covered in the written examination. Applied Mathematics To become PhD candidates, students must first pass a written preliminary examination (normally before the end of the first year of study) on two subjects: advanced calculus and linear algebra. Students must also submit a thesis proposal, and pass an oral examination on the thesis proposal and two minor subjects. The oral examination should normally take place before the end of the second year of study. Probability and Statistics To become PhD candidates, students must pass an oral qualifying examination on one major subject and two minor subjects (normally no later than the end of the second year of study). For Probability students, the major subject is Probability while the two minor subjects would be Statistics and an area in Mathematics or an appropriate area outside Mathematics. For Statistics students, the major subject is Statistics while the two minor subjects would be Probability and an area in Mathematics or an appropriate area outside Mathematics.
Thesis Research
Registration in MATH 6990; and
Presentation and oral defense of the MPhil thesis.
Registration in MATH 7990; and
Presentation and oral defense of the PhD thesis.
Last update: 1 June 2023
Scientific Computation Concentration
In addition to the existing program requirements, students who opt for the Scientific Computation concentration are required to:
MPhil: Complete a minimum of 7 credits from the following course lists. PhD: Complete a minimum of 10 credits from the following course lists. The credits earned under the concentration will be counted toward the total credit requirements of the programs. All students must take MATH 6915 and MATH 6916. Credits earned from MATH 6915 can be repeated for up to 2 credits. All students must take at least one course of other departments (excluding MATH 6915 and MATH 6916) or one CSIC course.
Elective Courses
Conduct research in the area of scientific computation.
To qualify for admission, applicants must meet all of the following requirements. Admission is selective and meeting these minimum requirements does not guarantee admission.
Applicants seeking admission to a master's degree program should have obtained a bachelor’s degree from a recognized institution, or an approved equivalent qualification;
Applicants seeking admission to a doctoral degree program should have obtained a bachelor’s degree with a proven record of outstanding performance from a recognized institution; or presented evidence of satisfactory work at the postgraduate level on a full-time basis for at least one year, or on a part-time basis for at least two years.
Applicants have to fulfill English Language requirements with one of the following proficiency attainments:
TOEFL-iBT: 80 *
TOEFL-pBT: 550
TOEFL-Revised paper-delivered test: 60 (total scores for Reading, Listening and Writing sections)
IELTS (Academic Module): Overall score: 6.5 and All sub-score: 5.5 *
* Refers to scores in one single attempt only. Test at home option is not accepted.
Applicants are not required to present TOEFL or IELTS score if
their first language is English, or
they obtained the bachelor's degree (or equivalent) from an institution where the medium of instruction was English.
Apply online before the application deadlines.
For Hong Kong PhD Fellowship (HKPFS) Application (for PhD studies only):
Step 1 deadline at RGC (to obtain an HKPFS reference no. from RGC): 1 Dec 2024 (12noon, GMT+8) Step 2 deadline at HKUST: 1 Dec 2024 (11:59pm, GMT+8) Details please refer to https://fytgs.hkust.edu.hk/hkpfs
For 2025/26 Fall Term Intake (commencing in Sep 2025):
Non-local Applicants* Full-time: 1 Jun 2025
Local Applicants Full-time: 1 Jun 2025 Part-time: 1 Jun 2025
For 2024/25 Spring Term Intake (commencing in Feb 2025):
Non-local Applicants* Full-time: 1 Nov 2024
Local Applicants Full-time: 15 Dec 2024 Part-time: 15 Dec 2024
* Applicants are considered as non-local students if they hold (i) student visa/ entry permit; or (ii) visa under the Immigration Arrangements for Non-local Graduates (IANG) ; or (iii) dependent visa/entry permit who were 18 years old or above when they were issued with such visa/ entry permit by the Director of Immigration. For details on student visa/ entry permit requirements, please click here .
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Students are required to complete MATH 6771. The 1 credit earned from MATH 6771 cannot be counted toward the credit requirements. PhD students who are HKUST MPhil graduates in Mathematics and have completed MATH 6771 before may be exempted from taking MATH 6771, subject to prior approval of the Department Head or Department PG Coordinator.
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Faculty-wise, BHU has extended offers to 22 distinguished professors through its Visiting Faculty Program, including 15 from prestigious global institutions. Over 250 faculty members have been granted Rs 2.2 crores in international travel support, while 1,348 educators have utilised more than Rs 14.8 crores from the Professional Development Fund under the IoE scheme.