Program Overview

High Performance Computing (M.Sc. / P.Grad.Dip.)

NFQ Level 9

Overview

The M.Sc. in High-Performance Computing is a one year full-time programme run by the School of Mathematics at Trinity College Dublin. The degree provides practical training in the emerging field of high-performance technical computing, which has applications in scientific simulation and mathematical modelling of systems in areas ranging from telecommunications to financial markets.

Course Details

• Awards: NFQ Level 9
• Next Intake: September 2025
• Course Coordinator: Prof. Kirk Soodhalter
• Closing Date: 31st July 2025

Admission Requirements

Applicants should normally have a first or upper second-class (2.1) degree in a subject with a significant mathematical component and should have some knowledge of computing and numerical simulation methods.

English Language Requirements

All applicants to Trinity are required to provide official evidence of proficiency in the English language. Applicants to this course are required to meet Band B (Standard Entry) English language requirements.

Course Fees

For a full list of postgraduate fees, please refer to the relevant section.

Course Structure

The M.Sc. in High Performance Computing is a one-year full-time taught Masters degree. To complete your M.Sc. studies, you should take a total of 60 ECTS units of coursework plus a 30 ECTS project, making a total of 90 ECTS. Many modules will have a written exam in the summer examination period. Most modules include some amount of continuous assessment.

Course Content

Course topics range from computer architecture, software optimisation, and parallel programming through to classical simulation and stochastic modelling. Application areas include simulation of physical, chemical and biological systems, financial risk management, telecommunications performance modelling, optimisation and data mining. The course has a number of optional elements, allowing specialisation in application areas.

Career Opportunities

This programme equips students with the combination of programming skills and mathematical insight to enable them to go on to careers or academic research in large-scale modelling, simulation or numerical multi-core software development. Successful graduates of the course go on to careers in technical and scientific computing and modelling, either in industrial or academic positions. A substantial number of graduates begin research towards their Ph.D. directly after completing the course, studying topics as diverse as astrophysics, biomolecular modelling, fluid mechanics, and financial mathematics.

Is This Course For Me?

The course is aimed at graduates with a degree in a technical discipline such as mathematics, physics, engineering, chemistry or mathematical finance. No prior programming experience is assumed but some familiarity with the concepts is useful. A background in basic mathematical concepts is also important.

Testimonial

What I enjoy most is the vibrant academic environment, where I get to collaborate with brilliant minds on cutting-edge projects. I love how my course bridges theory and real-world application, challenging me to push the limits of computational performance. It gives me the technical depth and industry connections to take my career to the next level.

Seeshuraj Bhoopalan

Graduate

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