The MSc in Computational Engineering is for students seeking to acquire the necessary skills to develop and apply computational methods for performing virtual simulations of a wide range physical problems, including solid mechanics, fluid dynamics, wave propagation and multi-physics.
Applicants to this MSc are usually students with a background in an Engineering (mechanical, aerospace, civil or electrical) or Science (mathematics, physics) discipline. This is a multidisciplinary programme, with modules that are complementary to those seeking to develop computational engineering skills to further their careers in Engineering and Science.
Students will develop solid programming skills and they will be able to tailor their degree by choosing one of the three available specialisations:
Software tools: Students will specialise in the development of computational software as well as the utilisation of commercial software for solving real-life engineering and scientific problems.
Data-Driven methods: Students will specialise in the integration of numerical methods and machine learning techniques with big data for solving real-life engineering and scientific problems.
Numerical techniques: Students will specialise in the development and analysis of modern computational methods with particular emphasis on the research aspect.
The MSc in Computational Engineering is one of the three Computational MSc courses offered by Swansea University. See the full list of programmes: Computational MSc courses
Why Computational Engineering at Swansea?
Swansea University has been a world-leading institution in Computational Engineering since the 1960s, when Professor Zienkiewicz joined Swansea University. Professor Zienkiewicz is internationally recognised as the "Father of the Finite Element Method" and founded the International Journal of Numerical Methods in Engineering and the UK Association for Computational Mechanics. Since then, Swansea University has maintained a privileged international position in the field of Computational Engineering.
The MSc in Computational Engineering is advised by an Industrial Steering Committee with industrial experts on computational engineering. The Industrial Steering Committee includes:
- Peritus International
- Pebble Engineering
The MSc Computational Engineering is taught by world-leading academics from the Zienkiewicz Institute for Modelling, Data and AI at Swansea University. These academics have a broad experience in creating new numerical methods and delivering computational tools that have been adopted by industry, including Airbus, BAE Systems, Chevron, NASA, SEAT, Siemens, Volkswagen.
In addition, these academics have written famous books in the field of Computational Engineering, and they have important positions in national and international associations in the field.
Students of the MSc Computational Engineering will be able to choose the topic of their dissertation among a wide range of themes. Students will have free access to all the software required to undertake their studies, both at PCs within the University and at home. For their dissertation they will also have access to the high-performance computing facilities available at Swansea, including the Impact Cluster and the Supercomputing Wales facilities at Swansea, with a total of 4,920 cores and 47 Tb of RAM memory.
Did you know? Civil Engineering at Swansea is ranked:
- Top 201-230 in the World for Engineering – Civil & Structural (QS World University Rankings 2023)
- UK Top 25 for Research Quality/Rating (The Times Good University Guide 2023)
- 100% world-leading and internationally excellent environment - Research Excellence Framework (REF) 2021
- Civil Engineering at Swansea a key centre for research and training in computational mechanics and engineering
- We have pioneered many techniques used in commercial simulation software today
Why study Computational Engineering?
Computer modelling and simulation is nowadays a tool that is widely employed in industry, not only to complement experiments and theory, but also as a tool for discovery. The field is quickly growing due to the ever-increasing complexity of the problems faced by industry and society. These problems include the need to mitigate the climate change, the need to engineer new materials and to optimise components, systems, and processes, just to name a few.
Addressing these challenges is only possible by using computational engineering to complement experimental work. Computational tools also provide a unique avenue for companies to reduce the time-to-market and time-to-manufacture of their products. In the current digital era, the use of big data and machine learning to constantly update the models has also opened the door to the development of digital twins in many areas of Engineering and Science.
The MSc Computational Engineering will equip students with the necessary skills to develop computational tools for the challenges of the 21st century.
Computational Engineering Employment Opportunities
Graduates of the MSc Computational Engineering have a wide range of opportunities. They can access jobs in industry or academia, depending on their interests.
Due to the unique skills of a Computational Engineer, the expected salary is usually higher than a standard Engineer. For instance, in the UK, the average salary of a Computational Engineering job in November 2022 is £43K, whereas the average salary of an Engineering job is £38K. It is worth noting that employers seeking for graduates use either “Computational Engineer”, “Modelling Engineer” or “Simulation Engineer” in their descriptions.
Companies that offer jobs to Computational Engineers include some of the most famous brands worldwide, namely Alphabet, Amazon, Apple, Boeing, Chevron, Coca-Cola, ExxonMobil, General Dynamics, HP, IBM, Intel, Meta, Microsoft, Nike, Pfizer, Tesla.
After graduation, some students prefer to pursue a PhD in Computational Engineering. Our graduates have gone on to pursue PhDs in many leading Universities worldwide and many Swansea graduates hold research or academic positions in prestigious Universities and R&D centres.