Financial & Computational Mathematics

Course Outline

Our postgraduate Financial and Computational Mathematics programme equips graduates with the skills necessary to pursue a successful career in quantitative finance. Modern financial technology is based upon sophisticated computational techniques for the modelling of asset and market movements, and the valuation of financial derivatives. This course provides a solid grounding in computational finance along with machine learning techniques and includes a team-based research project with opportunities to work with our industry partners.

Programme Structure

Part I (60 credits)

Core Modules (45 credits):

MF6010 Probability Theory in Finance (10 credits)

MF6011 Derivatives, Securities, and Option Pricing (5 credits)

MF6012 Computational Finance I (5 credits)

MF6013 Computational Finance II (5 credits)

MF6014 Topics in Financial Mathematics (5 credits)

MF6015 Continuous-Time Financial Models (5 credits)

AM6004 Numerical Methods and Applications (5 credits)

CS6322 Optimisation (5 credits)



Elective Modules (Choose 15 credits):

AM4062 Applied Stochastic Differential Equations (5 credits)

AM6007 Scientific Computing with Numerical Examples (5 credits)

AM6019 Partial Differential Equations (5 credits)

ST4400 Data Analysis II (5 credits)

ST6040 Machine Learning and Statistical Analytics I (5 credits)

ST6041 Machine Learning and Statistical Analytics II (5 credits)

CS6503 Introduction to Relational Databases (5 credits)



Part II (30 credits):

MF6016 Dissertation in Financial and Computational Mathematics (30 credits)

Requirements

- Candidates must have obtained at least a 2.2 degree or equivalent in the mathematical sciences or another quantitative subject.



- Candidates who have obtained at least a 2.2 honours degree in Engineering or Physics will be considered and should be able to demonstrate to the Course Coordinator some prior experience of probability and statistics, linear algebra, multivariate calculus, ordinary differential equations, and programming.



- Candidates, for whom English is not their primary language, should possess an IELTS of 6.5 (or TOEFL equivalent) with no less than 6.0 in each individual category.



- All candidates must be ultimately approved by the Course Coordinator.



For Applicants with Qualifications Completed Outside of Ireland

Applicants must meet the required entry academic grade, equivalent to Irish requirements. For more information see our Qualification Comparison page.



International/Non-EU Applicants

For full details of the non-EU application procedure visit our how to apply pages for international students.



- In UCC, we use the term programme and course interchangeably to describe what a person has registered to study in UCC and its constituent colleges, schools, and departments.



- Note that not all courses are open to international/non-EU applicants, please check the fact file above. For more information contact the International Office.



English Language Requirements

Applicants who are non-native speakers of the English language must meet the university-approved English language requirements. Visit our PG English Language Requirements page for more information.

Closing Date: Rolling deadline. Open until all places have been filled. Early application is advised.



Non-EU Closing Date: Open until all places have been filled or no later than 15 June. Early application is advised.

A variety of assessment methods are used during this course. In addition to the traditional end-of-year written examinations, you will undertake a series of individual and group assignments and projects during the year in the areas of both management accounting and information systems.


In addition, an applied research project is undertaken in groups by all students during the second teaching term, culminating with a series of group presentations to leading industry experts who in turn provide invaluable feedback and advice to each student group.


The IS6215 Business Research and Communications Skills module (10 credits), which forms part of the course syllabus, is an invaluable tool for you in preparing for such presentations.

1 year full-time.

Start Date: 8th September 2025.

Career Opportunities

Past graduates of this programme have been recruited to risk management (Acadia, China Reinsurance Corporation), regulatory (FinTru, KBRA), and wealth management/investment roles (Fidelity). They have also progressed to SFI-funded study at PhD level in the application of machine learning to finance. This programme will prepare you for a broad spectrum of roles in the financial sector and particularly in quantitative finance, risk analysis, and investment banking.



Skills and Careers Information

Graduates will be prepared for quantitative roles in the financial services sector and particularly in investment banking, including roles in financial engineering, quantitative finance, investment analysis, and fund management. The programme also serves as a route to further study in this area.