phd computational finance

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PhD Computational Finance

• Ask a question
• Get a prospectus

Entry requirements

Fees and funding.

• What's next?

We offer research supervision for our PhD Computational Finance in the following fields: agent-based modelling of financial markets; computational risk management; high-frequency finance; and the use of computational-intelligence methods for investment decision making. We provide a vibrant research environment so our PhD students publish papers in prestigious international conferences and often attract the attention of industry and government; one of our PhD students was recently invited to present their research on term structure models to the Bank of England and many others get the opportunity to directly apply their research through internships at investment banks and hedge funds.

Our graduates have gone on to become quantitative analysts, portfolio managers and software engineers at various institutions, including major investment banks like HSBC and Mitsubishi UFJ Securities.

You can start this degree in October, January or April, either full-time or part-time. We also offer an MPhil and MSD in this area.

• We have an international reputation for leading-edge, interdisciplinary work combining economic and financial modelling with computational implementation.
• Our research is geared towards practical applications, and many of our academic staff have experience of applying their findings in industry and in advising the UK government.
• We are supported by Essex's highly rated Department of Economics, School of Computer Science and Electronic Engineering, and Essex Business School.

Our expert staff

Within our Centre for Computational Finance and Economic Agents (CCFEA), our PhD students are normally jointly supervised by academic staff in two of our constituent departments, in order to give you an interdisciplinary perspective to your topic of research.

Specialist facilities

CCFEA is based within our School of Computer Science and Electronic Engineering.

Our School provides twelve laboratories exclusively for computer science and electronic engineering students. Three of our software labs are open for 24 hours a day including weekends and you have free access to the labs except when there is a scheduled practical class in progress. Our labs are managed by an experienced and dedicated team of technical support staff who can assist you - for example, advising on how to overcome programming problems. Students also have access to our Bloomberg virtual trading floor in the Essex Business School.

Your future

Graduates of our Centre have gone on to become quantitative analysts, portfolio managers and software engineers at various institutions, including major investment banks like HSBC and Mitsubishi UFJ Securities.

We have an extensive network of industrial contacts through our City Associates Board and our alumni, while our expert seminar series gives you the opportunity to work with leading figures from industry. A number of our students have held internships with prestigious City institutions, such as HSBC, Old Mutual and the Bank of England.

UK entry requirements

International & eu entry requirements.

We accept a wide range of qualifications from applicants studying in the EU and other countries. Get in touch with any questions you may have about the qualifications we accept. Remember to tell us about the qualifications you have already completed or are currently taking.

Sorry, the entry requirements for the country that you have selected are not available here. Please select your country page where you'll find this information.

English language requirements

Course structure.

A research degree doesn't have a taught structure, giving you the chance to investigate your chosen topic in real depth and reach a profound understanding. In communicating that understanding, through a thesis or other means, you have a rare opportunity to generate knowledge. A research degree allows you to develop new high-level skills, enhance your professional development and build new networks. It can open doors to many careers.

We understand that deciding where and what to study is a very important decision for you. We'll make all reasonable efforts to provide you with the courses, services and facilities as described on our website and in line with your contract with us. However, if we need to make material changes, for example due to significant disruption, we'll let our applicants and students know as soon as possible.

Components are the blocks of study that make up your course. A component may have a set module which you must study, or a number of modules from which you can choose.

Each component has a status and carries a certain number of credits towards your qualification.

The modules that are available for you to choose for each component will depend on several factors, including which modules you have chosen for other components, which modules you have completed in previous years of your course, and which term the module is taught in.

Modules are the individual units of study for your course. Each module has its own set of learning outcomes and assessment criteria and also carries a certain number of credits.

In most cases you will study one module per component, but in some cases you may need to study more than one module. For example, a 30-credit component may comprise of either one 30-credit module, or two 15-credit modules, depending on the options available.

Modules may be taught at different times of the year and by a different department or school to the one your course is primarily based in. You can find this information from the module code . For example, the module code HR100-4-FY means:

COMPONENT 01: COMPULSORY

This module is for PhD students who are completing the research portions of their theses.

View Computational Finance and Economic Agents - Research on our Module Directory

The aim of undertaking your PhD within CCFEA is to become trained as am independent researcher who can critically assess other research work, and have a comprehensive knowledge of their subject area.

Our PhD programme is usually three to four years duration and all our students are initially registered as Mphil/PhD students, then transferred to the PhD in the first half of their second year of study if they have made satisfactory progress. In your second and third years, you work towards your PhD.

Dissertation

Within CCFEA, your PhD thesis is generally completed within three to four years and has a length of around 80,000 words.

Your PhD is awarded after your successful defence of your thesis in an oral examination, in which you are interviewed about your research by two examiners, at least one of whom is from outside Essex.

Home/UK fee

£4,712 per year

International fee

£17,900 per year

Fees will increase for each academic year of study.

Masters fees and funding information

Research (e.g. PhD) fees and funding information

What's next

We hold Open Days for all our applicants throughout the year. Our Colchester Campus events are a great way to find out more about studying at Essex, and give you the chance to:

• tour our campus and accommodation
• find out answers to your questions about our courses, graduate employability, student support and more
• talk to our Fees and Funding team about scholarship opportunities
• meet our students and staff

If the dates of our organised events aren’t suitable for you, feel free to get in touch by emailing [email protected] and we’ll arrange an individual campus tour for you.

2024 Open Days (Colchester Campus)

• Saturday 15 June 2024 - June Open Day
• Saturday 21 September 2024 - September Open Day
• Saturday 26 October 2024 - October Open Day

You can apply for this postgraduate course online . Before you apply, please check our information about necessary documents that we'll ask you to provide as part of your application.

We encourage you to make a preliminary enquiry directly to a potential supervisor or the Graduate Administrator within your chosen Department or School. We encourage the consideration of a brief research proposal prior to the submission of a full application.

We aim to respond to applications within four weeks. If we are able to offer you a place, you will be contacted via email.

For information on our deadline to apply for this course, please see our ‘ how to apply ' information.

Visit Colchester Campus

Set within 200 acres of  award-winning  parkland - Wivenhoe Park  and located two miles from the  historic city centre of Colchester – England's oldest recorded development. Our Colchester Campus is also easily reached from London and Stansted Airport in under one hour.

Virtual tours

If you live too far away to come to Essex (or have a busy lifestyle), no problem. Our 360 degree virtual tour allows you to explore the Colchester Campus from the comfort of your home. Check out our accommodation options, facilities and social spaces.

Exhibitions

Our staff travel the world to speak to people about the courses on offer at Essex. Take a look at our list of exhibition dates to see if we’ll be near you in the future.

At Essex we pride ourselves on being a welcoming and inclusive student community. We offer a wide range of support to individuals and groups of student members who may have specific requirements, interests or responsibilities.

The University makes every effort to ensure that this information on its programme specification is accurate and up-to-date. Exceptionally it can be necessary to make changes, for example to courses, facilities or fees. Examples of such reasons might include, but are not limited to: strikes, other industrial action, staff illness, severe weather, fire, civil commotion, riot, invasion, terrorist attack or threat of terrorist attack (whether declared or not), natural disaster, restrictions imposed by government or public authorities, epidemic or pandemic disease, failure of public utilities or transport systems or the withdrawal/reduction of funding. Changes to courses may for example consist of variations to the content and method of delivery of programmes, courses and other services, to discontinue programmes, courses and other services and to merge or combine programmes or courses. The University will endeavour to keep such changes to a minimum, and will also keep students informed appropriately by updating our programme specifications . The University would inform and engage with you if your course was to be discontinued, and would provide you with options, where appropriate, in line with our Compensation and Refund Policy.

The full Procedures, Rules and Regulations of the University governing how it operates are set out in the Charter, Statutes and Ordinances and in the University Regulations, Policy and Procedures.

Related courses

• Colchester Campus

Want to quiz us about your course? Got a question that just needs answering? Get in touch with us on live chat!

• Course Finder
• Undergraduate study
• Postgraduate study
• Short courses and CPD
• International students
• Study online
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• General - [email protected]
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UW Computational Finance & Risk Management

Computational Finance & Risk Management

Exam proctors, application information, events calendar, cfrm highlights.

Alumni Spotlight: Ningning Wang

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Autumn 2022 Activities

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Parametric Fellowship Recipient Profile: Zeeshan Jawaid

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• Mathematical and Computational Finance @ Oxford
• Study with us

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 .

Email:  @email Phone:  +44 (0)1865 615234

Join us on  LinkedIn  or  sign up to our newsletter

DPhil Graduates

Graduate Education

Office of graduate and postdoctoral education, quantitative and computational finance, program contact.

Laura Czyzewski CODA Georgia Institute of Technology 756 West Peachtree St. NW Atlanta, GA 30308

Application Deadlines

• Early Round - Oct. 15
• Standard Round - Dec. 31
• Final Round for International candidates currently outside the US - March 15
• Final Round for US citizens, permanent residents and International candidates currently in the US - June 1
• Standard Round - Sept. 1
• Final Round - Oct. 1

Admittance Terms

Degree programs.

• Master's, Quantitative and Computational Finance

Interdisciplinary Programs

Quantitative and Computational Finance is offered by the College of Sciences, the College of Engineering, and Scheller College of Business. Students must select a home school from one of the following disciplines:

• Industrial and Systems Engineering
• Mathematics

Standardized Tests

TOEFL Requirements

• Institute Code: 5248
• Internet-based: 95, with minimum section scores of 19

IELTS Academic Requirements

• ≥ 7 (minimum band score for Reading, Listening, and Speaking is 6.5; minimum band score for Writing is 5.5)

GRE Requirements

• Institute Code: R5248
• General Test: Required

GMAT Requirements

• Institute Code: HWK-54-37

Application Requirements

• Three Letters of Recommendation

Program Costs

• Go to " View Tuition Costs by Semester ," and select the semester you plan to start. Graduate-level programs are divided into sections: Graduate Rates–Atlanta Campus, Study Abroad, Specialty Graduate Programs, Executive Education Programs
• Find the degree and program you are interested in and click to access the program's tuition and fees by credit hour PDF.
• In the first column, determine the number of hours (or credits) you intend to take for your first semester.
• Determine if you will pay in-state or out-of-state tuition. Learn more about the difference between in-state and out-of-state . For example, if you are an in-state resident and planning to take six credits for the Master of Architecture degree, the tuition cost will be $4,518.
• The middle section of the document lists all mandatory Institute fees. To see your total tuition plus mandatory fees, refer to the last two columns of the PDF.

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Computational Finance  

Project description.

Computational Finance is the key element for successful risk management at investment banks and hedge funds and it is also a growing area on the interface between finance, computational mathematics and applied probability. Pricing and hedging financial derivatives, evaluating risks of default for financial product and firms, satisfying requirements of the Basel Accord, etc. - all require sophisticated modelling and reliable calibration of the models. These aims cannot be achieved without efficient numerical techniques which form the area of computational finance.  The project will aim at developing new, efficient computational techniques related to finance. 

Eligibility/Entry Requirements:  We require an enthusiastic graduate with a 1st class degree in Mathematics, preferably at MMath/MSc level (in exceptional circumstances a 2:1 class degree, or equivalent, can be considered). We are expecting that the successful applicant has a good background in Probability and Stochastic Analysis, some knowledge of Finance and has exceptional computational skills.

For any enquiries please email: [email protected]

More information about Michael

Supervisor contacts

Prof Michael Tretyakov

Related research centre or theme

Numerical and Applied Analysis

Computational Statistics and Machine Learning

See all PhD funding opportunities

More information

Full details of our Maths PhD

How to apply to the University of Nottingham

School of Mathematical Sciences

The University of Nottingham University Park Nottingham, NG7 2RD

For all enquiries please visit: www.nottingham.ac.uk/enquire

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Unable to find any suggestions for your query...

The Essex website uses cookies. By continuing to browse the site you are consenting to their use. Please visit our cookie policy to find out which cookies we use and why. View cookie policy.

PhD Computational Finance

• Ask a question
• Get a prospectus

Entry requirements

Fees and funding.

• What's next?

We offer research supervision for our PhD Computational Finance in the following fields: agent-based modelling of financial markets; computational risk management; high-frequency finance; and the use of computational-intelligence methods for investment decision making. We provide a vibrant research environment so our PhD students publish papers in prestigious international conferences and often attract the attention of industry and government; one of our PhD students was recently invited to present their research on term structure models to the Bank of England and many others get the opportunity to directly apply their research through internships at investment banks and hedge funds.

Our graduates have gone on to become quantitative analysts, portfolio managers and software engineers at various institutions, including major investment banks like HSBC and Mitsubishi UFJ Securities.

You can start this degree in October, January or April, either full-time or part-time. We also offer an MPhil and MSD in this area.

• We have an international reputation for leading-edge, interdisciplinary work combining economic and financial modelling with computational implementation.
• Our research is geared towards practical applications, and many of our academic staff have experience of applying their findings in industry and in advising the UK government.
• We are supported by Essex's highly rated Department of Economics, School of Computer Science and Electronic Engineering, and Essex Business School.

Our expert staff

Within our Centre for Computational Finance and Economic Agents (CCFEA), our PhD students are normally jointly supervised by academic staff in two of our constituent departments, in order to give you an interdisciplinary perspective to your topic of research.

Specialist facilities

CCFEA is based within our School of Computer Science and Electronic Engineering.

Our School provides twelve laboratories exclusively for computer science and electronic engineering students. Three of our software labs are open for 24 hours a day including weekends and you have free access to the labs except when there is a scheduled practical class in progress. Our labs are managed by an experienced and dedicated team of technical support staff who can assist you - for example, advising on how to overcome programming problems. Students also have access to our Bloomberg virtual trading floor in the Essex Business School.

Your future

Graduates of our Centre have gone on to become quantitative analysts, portfolio managers and software engineers at various institutions, including major investment banks like HSBC and Mitsubishi UFJ Securities.

We have an extensive network of industrial contacts through our City Associates Board and our alumni, while our expert seminar series gives you the opportunity to work with leading figures from industry. A number of our students have held internships with prestigious City institutions, such as HSBC, Old Mutual and the Bank of England.

UK entry requirements

International & eu entry requirements.

We accept a wide range of qualifications from applicants studying in the EU and other countries. Get in touch with any questions you may have about the qualifications we accept. Remember to tell us about the qualifications you have already completed or are currently taking.

Sorry, the entry requirements for the country that you have selected are not available here. Please select your country page where you'll find this information.

English language requirements

Course structure.

A research degree doesn't have a taught structure, giving you the chance to investigate your chosen topic in real depth and reach a profound understanding. In communicating that understanding, through a thesis or other means, you have a rare opportunity to generate knowledge. A research degree allows you to develop new high-level skills, enhance your professional development and build new networks. It can open doors to many careers.

We understand that deciding where and what to study is a very important decision for you. We'll make all reasonable efforts to provide you with the courses, services and facilities as described on our website and in line with your contract with us. However, if we need to make material changes, for example due to significant disruption, we'll let our applicants and students know as soon as possible.

Components are the blocks of study that make up your course. A component may have a set module which you must study, or a number of modules from which you can choose.

Each component has a status and carries a certain number of credits towards your qualification.

The modules that are available for you to choose for each component will depend on several factors, including which modules you have chosen for other components, which modules you have completed in previous years of your course, and which term the module is taught in.

Modules are the individual units of study for your course. Each module has its own set of learning outcomes and assessment criteria and also carries a certain number of credits.

In most cases you will study one module per component, but in some cases you may need to study more than one module. For example, a 30-credit component may comprise of either one 30-credit module, or two 15-credit modules, depending on the options available.

Modules may be taught at different times of the year and by a different department or school to the one your course is primarily based in. You can find this information from the module code . For example, the module code HR100-4-FY means:

COMPONENT 01: COMPULSORY

This module is for PhD students who are completing the research portions of their theses.

View Computational Finance and Economic Agents - Research on our Module Directory

The aim of undertaking your PhD within CCFEA is to become trained as am independent researcher who can critically assess other research work, and have a comprehensive knowledge of their subject area.

Our PhD programme is usually three to four years duration and all our students are initially registered as Mphil/PhD students, then transferred to the PhD in the first half of their second year of study if they have made satisfactory progress. In your second and third years, you work towards your PhD.

Dissertation

Within CCFEA, your PhD thesis is generally completed within three to four years and has a length of around 80,000 words.

Your PhD is awarded after your successful defence of your thesis in an oral examination, in which you are interviewed about your research by two examiners, at least one of whom is from outside Essex.

Home/UK fee

£4,712 per year

International fee

£17,900 per year

Fees will increase for each academic year of study.

Masters fees and funding information

Research (e.g. PhD) fees and funding information

What's next

We hold Open Days for all our applicants throughout the year. Our Colchester Campus events are a great way to find out more about studying at Essex, and give you the chance to:

• tour our campus and accommodation
• find out answers to your questions about our courses, graduate employability, student support and more
• talk to our Fees and Funding team about scholarship opportunities
• meet our students and staff

If the dates of our organised events aren’t suitable for you, feel free to get in touch by emailing [email protected] and we’ll arrange an individual campus tour for you.

2024 Open Days (Colchester Campus)

• Saturday 15 June 2024 - June Open Day
• Saturday 21 September 2024 - September Open Day
• Saturday 26 October 2024 - October Open Day

You can apply for this postgraduate course online . Before you apply, please check our information about necessary documents that we'll ask you to provide as part of your application.

We encourage you to make a preliminary enquiry directly to a potential supervisor or the Graduate Administrator within your chosen Department or School. We encourage the consideration of a brief research proposal prior to the submission of a full application.

We aim to respond to applications within four weeks. If we are able to offer you a place, you will be contacted via email.

For information on our deadline to apply for this course, please see our ‘ how to apply ' information.

Visit Colchester Campus

Set within 200 acres of  award-winning  parkland - Wivenhoe Park  and located two miles from the  historic city centre of Colchester – England's oldest recorded development. Our Colchester Campus is also easily reached from London and Stansted Airport in under one hour.

Virtual tours

If you live too far away to come to Essex (or have a busy lifestyle), no problem. Our 360 degree virtual tour allows you to explore the Colchester Campus from the comfort of your home. Check out our accommodation options, facilities and social spaces.

Exhibitions

Our staff travel the world to speak to people about the courses on offer at Essex. Take a look at our list of exhibition dates to see if we’ll be near you in the future.

At Essex we pride ourselves on being a welcoming and inclusive student community. We offer a wide range of support to individuals and groups of student members who may have specific requirements, interests or responsibilities.

The University makes every effort to ensure that this information on its programme specification is accurate and up-to-date. Exceptionally it can be necessary to make changes, for example to courses, facilities or fees. Examples of such reasons might include, but are not limited to: strikes, other industrial action, staff illness, severe weather, fire, civil commotion, riot, invasion, terrorist attack or threat of terrorist attack (whether declared or not), natural disaster, restrictions imposed by government or public authorities, epidemic or pandemic disease, failure of public utilities or transport systems or the withdrawal/reduction of funding. Changes to courses may for example consist of variations to the content and method of delivery of programmes, courses and other services, to discontinue programmes, courses and other services and to merge or combine programmes or courses. The University will endeavour to keep such changes to a minimum, and will also keep students informed appropriately by updating our programme specifications . The University would inform and engage with you if your course was to be discontinued, and would provide you with options, where appropriate, in line with our Compensation and Refund Policy.

The full Procedures, Rules and Regulations of the University governing how it operates are set out in the Charter, Statutes and Ordinances and in the University Regulations, Policy and Procedures.

Related courses

• Colchester Campus

Want to quiz us about your course? Got a question that just needs answering? Get in touch with us on live chat!

• Course Finder
• Undergraduate study
• Postgraduate study
• Short courses and CPD
• International students
• Study online
• Apprenticeships
• Summer Schools
• Essex living
• Essex Sport
• Southend Campus
• Loughton Campus
• Student facilities
• Student services
• Research excellence
• Research showcase
• Media requests
• Research Excellence Framework (REF)
• Research institutes and centres
• Departments
• How to pay your fees
• General - [email protected]
• Undergraduate - [email protected]
• Postgraduate - [email protected]
• +44 (0) 1206 873333
• University of Essex
• Wivenhoe Park
• Colchester CO4 3SQ

• Accessibility
• Our privacy statements
• Our transparency return
• Modern slavery and human trafficking

Frequently Asked Questions

How do i apply to the mathematical and computational finance program.

Refer to the ICME admissions webpages for all details and questions on applying: https://icme.stanford.edu/admissions

Can you tell me in advance if my application will be competitive?

We get too many applications to discuss this information during the process, or if the application is incomplete. It is your responsibility to ensure your completed application is received before the deadline. Apply and await the results.

Will sending supplemental emails and materials help my chances of Admissions?

No. These will not be considered and will have no influence on the Admissions process.

When should I take the GRE? Do you have minimum scores?

The GRE is not required and will not be accepted as part of any ICME graduate application for 23-24.

Should I hire an admissions consultant? Should I seek assistance in writing my essay?

No. Admissions consultants will not improve your chances and may cause your application to violate the Stanford Honor Code. You may edit your essays with the advice of others, but you must author the essays yourself. Submitting work that is not your own is a violation of the Stanford Honor Code.

What are you looking for?

Simply put: a solid mathematics background and a passion for finance!

Do I need to have work experience in finance?

Work experience can be a great indicator of your passion. It is not required however.

Does it help my admission chances to contact faculty or staff to make my case?

You are welcome to contact Stanford faculty and staff if you have specific questions not addressed herein. As a general rule such contact is not required and will not influence your Admissions process.

What courses should I take as a future applicant?

We can’t make specific course recommendations but a solid math background is required. Many of our applicants have succeeded in taking graduate level courses in Mathematics as undergraduates. Carefully consider our core curriculum, topics covered and related prerequisites.

What topics should I be prepared to study?

Linear Algebra, Probability, Statistics, Numerical Methods, Optimization, Computing in Python, C++, etc. We also offer refresher courses right before Autumn quarter. We also offer a placement test for candidates with a strong computing background. Closely study our required course lists and the related prerequisite topics.

What is the relationship between MCF and the Financial Mathematics program within the Stanford Statistics Department?

The Financial Mathematics program was managed from the Statistics department and was one of the oldest quantitative finance masters degrees and produced top graduates in both academia and industry. In 2014 we renamed the program MCF and relaunched it within the Stanford School of Engineering. In so doing we have built off of the Financial Mathematics core strengths and updated the curriculum to be positioned along current trends in computer science, data science/machine learning, numerics etc… at Stanford and more generally. We consider ourselves to have a startup mentality with a long tradition and alumni base!

Can I take the GMAT instead of the GRE?

Neither the GRE nor the GMAT are required for application to ICME graduate programs in 23-24.

Do I need to take the TOEFL exam?

If you received either your undergraduate or graduate degree from a university in a non-native English-speaking country, then you must submit the TOEFL. There are no exceptions.

Should I apply to MCF in the Stanford School of Engineering or the MBA in the Stanford Graduate School of Business?

Both are terminal masters degrees offering specialization in Finance, world class recruiting opportunities, a strong cohort experience and joint club participation. In fact many MCF students will take GSB courses and many MBA students take courses in the School of Engineering. Some of our students have gone to study finance at the PhD level at the business school. Some of our students take jobs in more traditionally MBA type roles within finance. The MCF degree, at the end of the day, is an academically rigorous program which will instill solid foundational technical skills which can be applied directly in both quantitative and general finance careers.

Should I apply to MCF in ICME or the Financial Analytics M.S. concentration in Management Science and Engineering (MS&E)?

Both are terminal masters degrees offering specialization in Finance with world class recruiting opportunities. MCF is characterized by a strong cohort experience, an uncommonly rigorous academic curriculum and a strong track record of placement in banking, financial services, investment management, and other impactful roles in finance. The financial analytics degree is a part of Management Science and Engineering and has different degree requirements. Traditionally, financial analytics has had a more industrial orientation as compared to a more “Wall Street” orientation, as reflected in the differing courses.

I have heard it is hard to get into MCF. Should I instead apply to the General track or Data Science track in ICME?

All are terminal masters degrees offering specialization with world class recruiting opportunities. MCF is a competitive program, and that is reflected in recruiting and reputation in industry. A growing share of our students do end up going to technology or data science roles either in fintech or technology broadly. While other ICME tracks offer solid generalist preparation, MCF is a smaller cohort with a more focused orientation and well established tradition in industry.

Can I continue on to get a PhD at Stanford or academia?

MCF students who are interested in the PhD program will be required to apply through the regular ICME PhD application. There is no internal transition process between the MCF program and the CME-PhD program.

How does Stanford MCF compare to other quantitative finance masters programs?

Our goal is to train a small group of exceptionally talented students for high impact careers in quantitative finance academia and industry. We are not focused on growing enrollment numbers or preparing students for more generic roles. As a result we have uncommonly high student selectivity combined with hands on mentoring to guide students to get the most of the considerable campus wide resources and opportunity that Stanford brings. Our focus is rigorously quantitative and at a PhD level. For the right student this provides a uniquely strong foundational career launchpad. For a more generalist finance education we would refer students to the Stanford Graduate School of Business MBA program.

Is there help with Career Placements and Internships?

Stanford generally tends to attract students with an entrepreneurial drive and spirit in managing their careers. Beyond program advising there are placement events and resources at the MCF program level, at the ICME level including our Fall Xtend career event, advising and year round career events at the School of Engineering and the Career Development Center at the Stanford level. Beyond formal online application systems and on campus structured recruiting exams, there tends to be unstructured recruiting in the form of student clubs and networking. On occasion Stanford students, including in our program, have also been known to start their own companies.

Can I Complete the Program Part-time?

Only as an HCP applicant, see ICME website:  https://icme.stanford.edu/admissions/program-details

What is the cost of Tuition?

A Stanford education is unfortunately not inexpensive. Please refer to the published school of Engineering tuition rates. Most students will complete the program in two years or 6 quarters, however exceptionally prepared students can manage an accelerated 5 quarter program.

Does Stanford link Scholarships and Financial Support to Admissions for MCF?

No. Admissions are conducted on a need blind basis. We do not engage in the practice of using offers of guaranteed financial support for admissions offers. Students are responsible for procuring their own funding via loans, scholarships, internships or other external sources. There are a very limited number of teaching or research assistantships; these are competitive and not guaranteed.

How long is the program?

6 quarters. Students must take their first 3 quarters Autumn, Winter, Spring and typically take an internship during their Summer quarter. For the second year students would generally take Autumn and Winter quarters. The second Spring though not required is a recommended option for those wishing to take more classes and especially project classes.

I Was Not Offered Admission, Why?

We get many more qualified applicants than we have spots. We also try to build a balanced cohort. We encourage you to strengthen your credentials and apply next year!

How many apply and are admitted?

We have designed the program to target approximately 10 students per cohort. The Financial Mathematics program, which was the predecessor to MCF, had 15 year history of uncommonly selective admissions. Since launching as MCF our admission rate is roughly around 5%

Will being in California instead of New York impact my job placement chances at a NY-based investment bank or hedge fund?

In recent years placement risk has not been a factor. Of course this cannot be guaranteed to continue, but we do teach a widely transferrable skill set. Our geography is a key strength of our program! Since we are small and not all of our graduates are focused on banking (academia, startups/VC, buyside/hedge funds) and Stanford is a target recruiting school for most tier 1 banks and funds, our students have strong interviewing prospects within banking and success in obtaining those roles with relatively minimal internal competition. Outside of banking, we are blessed with a strong buy side and entrepreneurial community which appeals to some of our students. The largest ranked geographical clusters of our alumni are 1) NYC Metro area 2) San Francisco Bay Area 3) London 4) Hong Kong and other major financial centers around the world.

What are your placement statistics?

We have a 100% placement rate for students desiring internships and full time industry employment in recent years. While this cannot be guaranteed without respect to employment conditions, our small size, long running reputation in industry, alumni network and broadly transferrable skill set have served our students well. We also have a strong academic placement history.

What are some finance companies that have offered internships and employment to MCF students in the past few years?

Goldman Sachs, Morgan Stanley, JP Morgan, Bank of America, Citigroup, Tudor Funds, Two Sigma Investments, Blackrock, GMO, Cubist Investments, Citadel and many others.

Have any more questions?

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PhD Computational Finance

University of essex, different course options.

• Key information

Course Summary

Tuition fees, entry requirements, university information, similar courses at this uni, key information data source : idp connect, qualification type.

PhD/DPhil - Doctor of Philosophy

Subject areas

Financial Modelling Modelling / Simulation Systems Computational Mathematics / Cybernetics Finance / Accounting (General)

Course type

We offer research supervision for our PhD Computational Finance in the following fields: agent-based modelling of financial markets; computational risk management; high-frequency finance; and the use of computational-intelligence methods for investment decision making. We provide a vibrant research environment, so our PhD students publish papers in prestigious international conferences and often attract the attention of industry and government; one of our PhD students was recently invited to present their research on term structure models to the Bank of England and many others get the opportunity to directly apply their research through internships at investment banks and hedge funds.

Our graduates have gone on to become quantitative analysts, portfolio managers and software engineers at various institutions, including major investment banks like HSBC and Mitsubishi UFJ Securities.

Your future

Graduates of our Centre have gone on to become quantitative analysts, portfolio managers and software engineers at various institutions, including major investment banks like HSBC and Mitsubishi UFJ Securities.

We have an extensive network of industrial contacts through our City Associates Board and our alumni, while our expert seminar series gives you the opportunity to work with leading figures from industry. Several our students have held internships with prestigious City institutions, such as HSBC, Old Mutual and the Bank of England.

UK fees Course fees for UK students

For this course (per year)

International fees Course fees for EU and international students

You will need a good master’s degree, or equivalent, in a related subject. A well-developed research proposal is also essential. You must be experienced in at least one high-level programming language (such as MATLAB, Java or Python).

The University of Essex prides itself on being at the forefront of change. It is an institution with a culture of boldness where creativity and curiosity in learning are both encouraged and expected. It’s a UK university, placing 36th and 32nd according to the Whatuni Student Choice Awards 2023 and the 2024 Complete University Guide rankings, respectively. At the University of Essex, students are taught by world-leading academics in a... more

MSc Financial Engineering and Risk Management

Full time | 1 year | 03-OCT-24

MSc Computational Finance

Mphil computational finance.

Full time | 3 years | 03-OCT-24

UCL Computer Science

Financial Computing and Analytics

• Publications

The Financial Computing and Analytics research group investigates socio-economic systems using methods from computer science, applied mathematics, computational statistics and network theory.

We investigate socio-economic systems using methods from computer science, applied and numerical mathematics, scientific computing, computational statistics, statistical physics and network theory. We build models for market and systemic risk and lay the foundations for the study of the new digital economy at the interface between technology and society. Our work is of importance to regulators, policy makers, citizens and companies.

Our group carries out world-class research in

• computational finance
• financial risk management
• blockchain technology
• digital economy
• decentralised finance
• systemic risk
• derivatives pricing
• model calibration
• agent-based models
• empirical finance
• market microstructure
• algorithmic trading
• high-frequency trading
• data science
• big data analytics
• data-driven modelling
• network analysis
• machine learning
• artificial intelligence
• price formation
• portfolio optimisation
• smart contracts

The left sidebar leads to the announcements of future  seminars  and recordings of past ones, our education offer, a comprehensive list of  publications  and a few examples of code  that we have developed. The right sidebar presents the group members and reports recent tweets. You may follow our latest research on a  blog  that we maintain on an external page.

In 2015, the Financial Computing and Analytics Group founded the UCL Centre for Blockchain Technologies . Tomaso Aste is the Scientific Director and Paolo Tasca is the Executive Director.

In 2012, the Financial Computing and Analytics Group co-founded the Systemic Risk Centre , which is hosted by the London School of Economics and Political Sciences and has been supported for its first 5 years by an ESRC grant. Our Head of Research Group Tomaso Aste is a member of the SRC Management Committee and several people of our group are Research Associates of the SRC.

Collaborations

We collaborate with the private and public financial services sector to provide outstanding graduates and postgraduates for careers in the financial industry or the government's regulatory bodies, including

• investment banks
• retail banks
• central banks
• hedge funds
• financial services technology firms
• insurance companies
• reinsurance companies
• stock exchanges
• alternative trading
• execution venues

We are always looking for new students and collaborators. We consider applications throughout the year and try to find the most suitable solution when we identify the possibility of a stimulating collaboration. For MSc, MRes and PhD opportunities, see the education page linked from the left sidebar.

Featured areas of research

• Blockchain technology
• Complexity in economics and finance
• Digital economy
• Machine learning in finance
• Statistical and stochastic modelling in finance
• Computable contracts
• Smart contracts

Includes honorary staff with teaching duties

Tomaso Aste Professor of Complexity Science Head of Research Group

Fabio Caccioli Professor of Complex Systems

Christopher Clack Professor of Blockchain and Smart Contracts

Guido Germano Professor of Computational Science

Yaacov Mutnikas Honorary Professor

Philip Treleaven Professor of Computer Science

Paolo Barucca Associate Professor

Paris Pennesi Honorary Associate Professor

Carolyn Phelan Associate Professor (Teaching)

Paolo Tasca Associate Professor

Nikhil Vadgama Associate Professor (Teaching) Jiahua Xu Associate Professor

Riaz Ahmad Lecturer (Teaching) 

S ilvia Bartolucci Lecturer

Maria del Rio-Chanona Lecturer

Nikan (Nick) Firoozye Lecturer (Teaching) 

Geoffrey Goodell Lecturer

David Vidal-Tomás Lecturer  

Associate academic staff Delmiro Fernandez-Reyes

Former academic staff Maxime Nicolas , Research Fellow, 2022-2023 Ye Sun ,   Research Fellow, 2021-2023 Giacomo Livan , Associate Professor, 2014-2023 Robert Smith , Associate Lecturer (Teaching), 2005-2023 Simone Righi , Lecturer, 2018-2020 Weihua Li , Research Associate, 2017-2020 Mircea Zloteanu , Research Associate, 2017-2018 Daniel Fricke , Lecturer, 2016-2018 Julius Bonart , Lecturer, 2016-2017 Sebastian del Baño Rollin , Senior Teaching Fellow, 2012-2014 William Shaw , Professor, 2011-2012 Honorary and visiting academics Sergio Álvarez-Teleña Marco Bardoscia Julija Bainiaksina Julius Bonart Stephen Emmott Daniel Fricke Michal Galas Denise Gorse Daniel Heller Giacomo Livan Piotr Karasinski Rosario Mantegna Peter Mitic Giuseppe Nuti Giles Pavey Paul Ormerod Simone Righi Martin Schoernig John Tang Stephen Weston Aric Whitewood Jack Wratten Blaž Žličar

Former honorary and visiting Ariane Chapelle , Honorary Reader, 2013-2023 Tiziana Di Matteo Gautam Mitra Paul Harrald Christian Hesse David Meinhart , 2014-2019 Jessica James , Honorary Professor, 2013-2018 Donald Lawrence , 2006-2018 William Shaw , Honorary Professor, 2012-2017

Other Francesco Caravelli Chris Marshall Giacomo Pietronero Yu Sun , Erasmus+ Visitor 2021-2022 Stacy Williams

Sabrina Aufiero Antonio Briola Pawel Chilinski Jose Gonzalez Jinsong Hao Kemal Ozan Andreas Koukorinis Mingtang Li Yinfei Li Jiaqi Liang Benjamin Loveless Afsaneh Mastouri Tim Ohlenburg Anahí Rodríguez-Martínez Yo-Der Song David Twomey Mihail Voicu Zexuan Yin

Financial Computing and Analytics Alumni Network LinkedIn group for present/former staff and PhD/MRes/MSc students associated with the UCL CS Financial Computing and Analytics Group Gabriel Borrageiro , PhD 2023 Haotian Gao , PhD 2023 Leo Carlos-Sandberg , PhD 2023 Dimitri Malandreniotis , PhD 2023 Fatih Özhamaratlı , PhD 2023 Isobel Seabrook , PhD 2023 Orowa Sikder , PhD 2023 Yuanrong Wang , PhD 2023 Henri Ashton , PhD 2022 Ye-Sheen Lim , PhD 2022 Andrew Mann , PhD 2022 Mohsen Naderi , PhD 2022 Pier Francesco Procacci , PhD 2022 Jeremy Turiel , PhD 2022 Anna Zaremba , PhD 2022 Maria Böker , PhD 2021 Lucio Idone , PhD 2021 Yinfei Li , PhD 2021 Samuel Stern , PhD 2021 Sonja Tilly , PhD 2021 Peter Divos , PhD 2020 Riccardo Marcaccioli , PhD 2020 Denis de Montigny , PhD 2020 Guido Previde Massara , PhD 2020 Amanah Ramadiah , PhD 2020 Adriano Soares Koshiyama , PhD 2020 Dorota Toczydłowska , PhD 2020 Eduard Sariev , PhD 2020 Julija Bainiaksina , PhD 2019 Samuel Palmer , PhD 2019 Ross Phillips , PhD 2019 Tharsis Pinto Souza , PhD 2019 Daniel Grigat , PhD 2018 Carolyn Phelan , PhD 2018 Sachapon Tungsong , PhD 2018 Blaž Žličar , PhD 2018 Peter Bebbington , PhD 2017 Alberto Ciacci , MRes 2017 Yiran Cui , PhD 2017 Federico Graceffa , MRes 2017 Marios Michailidis , PhD 2017 Volha Kolchyna , PhD 2017 Marios Michailidis , PhD 2017 Vytautas Savickas , PhD 2017 Bogdan Batrinca , PhD 2016 Annika Birch , PhD 2016 Kacper Chwialkowski , PhD 2016 Noemi Nava Morales , PhD 2016 Rickard Nyman , PhD 2016 Mininder Sethi , PhD 2016 Sergio Álvarez-Teleña , PhD 2015 Paul-Kilian Lamanna , MRes 2015 Joe Staines , PhD 2015 Ilya Zheludev , PhD 2015 Michal Galas , PhD 2014 Michael Kusnetsov , MRes 2014 Panagiotis Papakos , PhD 2014 Chris Bracegirdle , PhD 2013 M. Ayub Hanif , PhD 2013 Giuseppe Nuti , PhD 2008

Ricki Angel Teaching and Learning Administrator, MSc Computational Finance, MSc Financial Risk Management, MSc Financial Technology, MSc Emerging Digital Technologies

Ricki Angel Teaching and Learning Administrator [email protected] Telephone +44 20 7679 7287

Tweets by uclfincomp

• Computational Finance

The Department of Statistics is part of the Computational Finance Program at Purdue University. It provides students the mathematical and statistical theory and tools, the computational experience, and the financial knowledge that are the basis of today's investment finance industry, including derivative pricing, portfolio management, risk management, and their associated numerical methods. The weekly Computational Finance seminar brings in academic and industrial leaders from the financial world, providing valuable contacts for the students. Faculty from several other departments and schools, including Computer Science , Economics , Electrical and Computer Engineering , Industrial Engineering , Management , Mathematics , and Physics have taught in the program and participated in the seminars.

Our program is primarily tailored to applicants with an excellent mathematical background. An ideal applicant is expected to have taken an upper-division real analysis course, or an upper-division course in probability theory or mathematical statistics from an undergraduate mathematics or mathematical statistics program. Alternatively, a student who performed well in a graduate applied mathematics courses and shows promise of doing well in our required mathematics and statistics courses will also be considered an ideal applicant. Students should also have taken at least one course in linear algebra, and one applied upper-division course in statistical methodology.

Financial Support: There is a possibility of obtaining financial support for exceptionally strong applicants that includes half-time teaching assistantship and full payment of tuition.

Related Links:

• MS Statistics Degree with Specialization in Computational Finance
• MBA with Specialization in Computational Finance
• Department of Mathematics Computational Finance Program
• Computational Finance MS Degree

Purdue Department of Statistics, 150 N. University St, West Lafayette, IN 47907

Phone: (765) 494-6030, Fax: (765) 494-0558

© 2023 Purdue University | An equal access/equal opportunity university | Copyright Complaints

Trouble with this page? Disability-related accessibility issue ? Please contact the College of Science .

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Financial Engineering, M.S.

Sophisticated modeling and information technology now dominate the financial world. The theories and the practice of Finance are challenged today by complex financial and global systems and by dynamically changing regulatory environments and politics. A global world in transition creates both opportunities and challenges for financial engineers to adapt theoretical and financial constructs into profitable and innovative opportunities by creating innovative, custom-designed instruments in the marketplace.

At the NYU School of Engineering, we train our students to do exactly that: to engineer the future of finance and transform financial theory into practice. The MS in Financial Engineering program furnishes students with foundational knowledge in financial concepts. This knowledge then becomes a springboard to specialized fields where students can apply concepts to everything from derivatives risk finance to financial IT and algorithmic trading on Big Data.

About the Program

The Department receives a large number of applications every year. To be considered for admission into the MS in Financial Engineering program, students must have a Bachelor’s Degree from an accredited institution and proven proficiency in:

• Linear Algebra
• Probability Theory
• Multivariable Calculus (Advanced)
• Applied Statistics
• Computer Programming

Admission Requirements

• Official Transcripts
• Statement of Purpose
• 1-minute video
• 2 Letters Of Recommendation
• English Language Proficiency Testing, where applicable
• Online application
• $90 application fee

Learn more about Admission Requirements .

The average Quant GRE score of accepted students in Fall 2023 was 169.0/170, the Verbal GRE score was 158.3, and the GPA was 3.848.*

*Beginning in 2023, the GRE is optional and not required to be admitted to the NYU Tandon School of Engineering.

When applicable, applicants must also demonstrate English language proficiency to be determined by the TOEFL score.

The FRE department does not accept change-of-major requests. In all instances, students must formally apply to the program. Applicants must have demonstrated proficiency in the mathematical areas listed to be considered for admission. The Department offers both an online and an on-campus boot camp during the summer before formal coursework starts.  For program highlights and a video regarding further details on FRE admissions requirements, visit our  Prospective Students  page.

Undergraduate students are not allowed to take courses in the MS in Financial Engineering program, except for those in a combined BS/MS program.

Contact the Graduate Center for questions about the  application process, application status or to talk to an admissions counselor :

Office of Graduate Enrollment Management and Admissions NYU Tandon School of Engineering 458 Pike Road Huntingdon Valley, PA 19006

[email protected] Phone: (646) 997-3182

Contact the Department of Finance and Risk Engineering with your  academic questions, e.g., courses and curricula .

Department of Finance and Risk Engineering NYU Tandon School of Engineering 1 MetroTech Center North, 10th floor Brooklyn, NY 11201 [email protected] Tel: 646.997.3279 Fax: 646.997.3355

Professor Barry Blecherman General Advising [email protected]

Ms. Zahra Patterson Academic Planner, Degree Progress Report, and Graduation Audits [email protected]

Professor Agnes Tourin Capstone Advisement [email protected]

Students enrolled full-time will complete the program in 4 semesters (May) although some may accelerate the course load and graduate within 3 semesters. Our program also offers flexibility to attend part-time and extend the number of semesters.

To earn a Master of Science in Financial Engineering, students must complete 33 credits to qualify for graduation. The structure of the program is as follows:

• Bootcamp of 0 credits
• 5 core courses, each 3 credits
• General elective courses within FRE and closely related fields personalized by the student, totaling 13.5 credits
• 1 required applied lab worth 1.5 credits
• 1 capstone experience of 3 credits Read the Capstone Guidelines (PDF)
• Capstone assessment of 0 credits
• Bloomberg certification of 0 credits

Total # of credits: 33

There are also two options to participate in a Vertically Integrated Project (VIP)  (0 credits).

• Merger & Acquisition Outcome Prediction
• Active Portfolio Management with Machine Learning and Time Series Forecasting

Students must also complete the Bloomberg Market Concepts e-learning course and earn the Acknowledgement of Completion to qualify for graduation. The Department will support your efforts to complete the training program by providing many Bloomberg terminals and laboratory assistants to answer your questions. This is a zero-credit requirement, listed as FRE 5500.

In recent years, our MSFE students (100-150 students) have gone on to a variety of career paths with the help of our Career Placement Director. Most notably, these paths have included Desk Quant/Strategist, Risk Management Analyst/Associate, Trader, Quant Researcher, Technology/FinTech Analyst, Data Science Analyst, Quant Model Development/Quantitative Modeler, and Model Validation. 

Learn more about our employee outcome statistics .

CORE COURSES (15 CREDITS)

Required courses:.

FRE-GY6073: Introduction to Derivative Securities

FRE-GY6083: Quantitative Methods in Finance

FRE-GY6103: Valuation for Financial Engineering

Two of the following three courses:

FRE6023: Financial Economics

FRE6123: Financial Risk Management

FRE7773: Machine Learning in Financial Engineering

GENERAL ELECTIVES (13.5 CREDITS) 

Students may choose from any FRE courses to fulfill these focus areas* and general elective requirements. They may also elect to register for up to three (3) classes (maximum of one per semester) at select schools/programs at NYU. Courses outside FRE must be approved by the MS Financial Engineering academic advisor. Students may only enroll for courses at other schools of NYU that are not offered at the School of Engineering. Please review the NYU cross-school registration policy prior to submitting cross-registration requests.

View the complete list of FRE Courses

APPLIED LAB (1.5 CREDITS*)

Choose 1 lab from the following:

FRE-GY6811: Financial Software Laboratory

FRE-GY6821: 

FRE-GY6831: COMPUTATIONAL FINANCE LABORATORY (PYTHON)

FRE-GY6861: Financial Software Engineering Laboratory

FRE-GY6871: R in Finance

FRE-GY6883: Financial Computing

*For FRE-GY6883, 1.5 credits count as lab and 1.5 credits as elective.

FRE-GY6191: Advanced Topics in Financial Technology

Note: Waivers are possible.

REQUIRED CERTIFICATION (0 CREDITS)

FRE-GY5500: Bloomberg Certification

CAPSTONE (3 CREDITS)

Choose 1 capstone option:

I. INTERNSHIP

FRE-GY7021: Financial Engineering Capstone: Internship

Minimum 240 hours per semester;  FRE-GY7021 must be taken twice in order to fulfill the capstone requirement; 1 report to the faculty is required

II. PROJECT

FRE-GY7043: Financial Engineering Capstone: Project

Project under faculty supervision

III. THESIS

FRE-GY9973: MS Thesis in Finance & Risk Engineering

IV. SPECIAL TOPICS

3.00 credits (two courses of 1.5 credit each or a single 3.00 credit course) of courses marked “topics” or “special topics” in the FRE section of the school course catalog, with a capstone paper submitted to the capstone advisor.

In addition, please see the  Capstone Procedures and Requirements (PDF) .

CAPSTONE ASSESSMENT (0 CREDITS)

FRE-GY5990: Capstone Assessment

Vertically Integrated Projects (0 CREDITS)

Quick links.

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Shreya Gossain

Boubacar Diallo

Master of Science in Computational Finance

Global leader.

Carnegie Mellon's MSCF program is a global leader for applied quantitative finance coursework in New York City and Pittsburgh

Explore Career Paths

Interdisciplinary Curriculum

our full-time faculty members offer the math, finance, statistics and computer science you will need for success in quantitative finance

Learn about the MSCF Curriculum

over the last three years, 99% of our students accepted full-time positions within six months of graduation

A Seamless Program Experience

locations in Pittsburgh & New York City

Student Experience

Quantifiably Different

For 29 years, carnegie mellon university’s interdisciplinary, top-ranked master of science in computational finance program has prepared students for highly successful careers in quantitative finance..

• Request Information

Two Locations

in New York City and Pittsburgh Learn More

21 Full-time Faculty

dedicated to helping students succeed Faculty

99% Received Offers

within 3 months of their graduation Employment Statistics

Over 2000  employers globally

including 30 sell-side banks recruit from MSCF  CAREER PATHS

MSCF Adjunct Professor, Leif Andersen, named 2023 Financial Engineer of the Year

Mscf squarepoint fellows: fall 2023, mscf student launches podcast, mscf names new executive director, masters in financial engineering programs, mscf ny on the move.

Pittsburgh Location              Carnegie Mellon University, TCS Hall 5000 Forbes Avenue Pittsburgh, PA 15213 Office: (412) 268- 3629

New York City Location Carnegie Mellon University 88 Pine Street, 12th Floor New York, NY 10005 Office: (412) 268-8446

MSCF Admissions Carnegie Mellon University Pittsburgh, PA 15213 Phone: (412) 268-3679 [email protected]

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The Bioinformatics PhD Program is well established, with a long history of successful graduates in both academia and industry.  

• How to Apply
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• Transition from Master's to PhD
• Frequently Asked Questions

To apply for the Bioinformatics PhD Program, you must submit complete applications by December 1 for admission the following Fall term. Early applications are not allowed and will not be considered. 

Please visit the Rackham Graduate School web pages for additional information on applying. There you will also find information on how to respond to an offer of admission, plus tips and materials required for international applicants and incoming students.

If you are certain about pursuing a Bioinformatics PhD, then applications should be submitted directly to the Bioinformatics PhD Program ; there are more than 100 diverse affiliated faculty to choose from.

Applicants should be U.S. citizens or permanent residents. In addition, applicants with a background in quantitative sciences should consider applying directly. Separately, if you are transferring from another University of Michigan Program or have obtained an established University of Michigan mentor affiliated with the program, a direct application is most appropriate.

PIBS is an umbrella program that offers first-year PhD students flexibility in exploring opportunities in bioinformatics and thirteen other graduate programs. Through PIBS, students have the opportunity to rotate in, and potentially join the lab of a faculty mentor in another program; there are more than 500 diverse faculty to select from. PIBS students who list Bioinformatics as their primary choice must complete at least one rotation with a Bioinformatics-affiliated faculty member. After 10 months in PIBS, students officially join Bioinformatics (or one of the other programs). You can visit the PIBS website for more information.

Please note that reviewing admissions faculty for both PIBS and direct applications are the same. In addition, admitted applicants take the same Bioinformatics-specific courses and activities. See below for details on program diversity outreach, application materials, and funding.

Students who will have an MS in a relevant field (e.g. computer science, statistics, biostatistics, biology) from another university may request to have up to 6 credit-hours (two classes) waived. These classes may be used to help fulfill the core PhD requirements for biology (1 course), statistics (2 courses), and/or computing (1 course). To obtain approval, students need to send a detailed syllabus of the class(es) they took to the PhD directors along with their grade(s), which must be a B or better. The other PhD course requirements, including BIOINF-529 and two advanced bioinformatics courses, cannot be waived.

Most international Bioinformatics PhD applicants should apply through PIBS. However, some who are already embedded in a University of Michigan mentor lab affiliated with the program may be an appropriate fit for the direct Bioinformatics PhD program.

The TOEFL or IELTS exam is required unless Rackham Graduate School waiver requirements have been met. Criteria for English proficiency exemption can be found on the Rackham website . In addition, a list of required credentials from non-U.S. institutions for an application can be found here.

The Bioinformatics Graduate Program encourages applications from traditionally underrepresented minorities, students with disabilities, and those from disadvantaged backgrounds. There are numerous funding opportunities and resources on campus to contribute to students overall well-being while pursuing studies. Several resources available to students can be found on the Rackham Graduate School Diversity, Equity, and Inclusion website .

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All application materials should be submitted electronically when possible. Applicants must meet  Rackham's Minimum Requirements for Admission . The  online application form  can be found on the Rackham Admissions webpages. The application is available in early September through the deadline. 

• GPA, minimum 3.2/4.0 (exceptions may be made if deemed appropriate)
• Letters of recommendation (3 required): Please be aware that submitting only the Rackham Recommendation for Admission Form is insufficient; forms must be accompanied by a letter from the recommender. All letters are due by the application deadline. Without them, applications will not be considered complete or reviewed by the Program Admissions Committee.
• Statement of Purpose: The Statement of Purpose should be a concise, well-written statement about your academic and research background, your career goals, and how Michigan's graduate program will help you meet your career and educational objectives.
• Personal Statement: The Personal Statement should be a concise, well-written statement about how your personal background and life experiences, including social, cultural, familial, educational, or other opportunities or challenges, motivated your decision to pursue a graduate degree at the University of Michigan. This is not an Academic Statement of Purpose, but a discussion of the personal journey that has led to your decision to seek a graduate degree.
• Transcripts: Please submit unofficial transcripts electronically with your online application
• GRE scores are no longer included as part of admission
• Applicants whose native language is not English must demonstrate English proficiency via either the TOEFL or IELTS exam. The institution code is 1839. Other exams may not be substituted. Rackham Graduate School offers a full explanation of this requirement , including exemption criteria. Please contact Rackham directly ( [email protected] ) with questions.

Diversity is a key component of excellence, especially for solving the complex biomedical challenges that our field of computational medicine and bioinformatics faces. We believe that all people—regardless of background, race, religion, sexual/gender orientation, age or disability—deserve an equitable opportunity to pursue the education and career of their choice.

The Bioinformatics Graduate Program will provide tuition, healthcare coverage, and a stipend on a 12-month basis. This level of support will be maintained throughout a student's tenure in the Program, provided s/he remains in good academic standing and makes reasonable progress towards the degree as determined by the Graduate Directors, with faculty input. It is expected that the student will be supported directly by the mentor's laboratory, beginning in the second year. The expected time to degree is typically 5-6 years.

The U-M MS program is a terminal degree program. If you are interested in the Bioinformatics PhD Program, you must submit a new application. If you are a Bioinformatics MS student who is in good academic standing and has identified a Bioinformatics affiliated faculty mentor, you may apply for admission directly to the PhD Bioinformatics Program for the Winter term. Reviewing faculty take all application components into account and mentors are prepared to take both academic and financial responsibility for their trainees.

Eligibility: Only current or recently graduated University of Michigan Master’s students are eligible. Before applying, students must have completed more than half of all required courses, with at least six credits from the Bioinformatics Program.

Application deadline: October 1

The online application form can be found on the Rackham Admissions webpages. The application is available in early September through the deadline.

• Letters of recommendation: Please be aware that submitting only the Rackham Recommendation for Admission Form is insufficient; forms must be accompanied by a letter from the recommender. If you wish to include three letters from your original application, only one additional letter is needed. It must be from the DCMB faculty member who will serve as your primary mentor. The letter should state clearly that the mentor takes responsibility for your funding upon admission. Alternatively, you may wish to obtain three new letters of recommendation. The Admissions Committee strongly encourages you to include letters from those familiar with your research and coursework obtained while pursuing your Master’s degree. Of these, one must be from the faculty member who will serve as your primary mentor. The letter should state clearly that the mentor takes responsibility for your funding upon admission.
• Statement of Purpose: The Statement of Purpose should be a concise, well-written statement about your academic and research background, your career goals, and how the PhD Program will help you meet your career and educational objectives.
• Transcripts: Only a current, unofficial U-M transcript is necessary. You do not need to re-submit materials included with your Master’s application.
• TOEFL: If you submitted TOEFL scores when applying to the Master’s Program, additional test scores are not needed.

Bioinformatics consists of a mathematical and/or statistical analysis of a biomedical problem using computation. We define bioinformatics widely and include traditional bioinformatics areas such as for examples, systems biology, genomics, proteomics, plus statistical and evolutionary genetics, clinical informatics, and protein modeling.

As an interdisciplinary field, Bioinformatics attracts graduate students from mathematics, statistics, physics, computer science, biomedical engineering, chemistry, biochemistry and biology. Most incoming students have both a major in one and a minor in another discipline. In recent years students have entered with undergraduate training in bioinformatics or computational biology.

Each student obtains individual counseling by one of the two graduate program directors upon arrival and throughout their academic career. As Bioinformatics is still developing, new courses are added all the time. Current students are encouraged to contact the Program Directors about courses that may be relevant to their studies and are not listed on the website (esp. if they are new or infrequently offered).

In most cases, we recommend you apply to the PIBS program, as it provides flexibility in classes, funding, and a central admission for many biomedical programs. If you have no or very little biology background, please contact our Student Services Representative as to whether a direct application would be better. Current student who are considering transferring areas of study should also contact the Bioinformatics Graduate Office.

There is no need to apply both direct and through PIBS, as the same committee sees your applications.

For most students, thesis work includes computing, reading, and writing. A small group also participates in wet laboratory work. Please check both the research areas and student webpages for an overview of the varied subjects addressed in research and student theses.

Many of our graduate students obtain academic postdoctoral fellowships and go on to faculty positions. Quite a significant number of graduates go into non-academic professions such as small or large biotech companies. Some have founded their own business, and others apply their analytical skills in companies unrelated to bioinformatics. For a current list of graduate placement, please visit the alumni pages.

No. If you want to get a PhD, directly apply to the PhD Program.

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