Scientific and Data Intensive Computing MSc

Scientists and engineers are tackling ever more complex problems, most of which do not admit analytical solutions and must be solved numerically. Numerical methods can only play an even more important role in the future as we face even bigger challenges. Therefore, skilled scientific programmers are in high demand in industry and academia and will drive forward much of the future economy. This MSc programme offers an in-depth and rigorous training in computational science, designed to equip students with advanced computational skills applicable across a wide range of scientific and engineering disciplines. Combining state-of-the-art computational techniques with real-world scientific problems, this programme develops highly skilled computational scientists and engineers who can harness the power of numerical methods and data-intensive approaches to solve complex problems. Students will gain expertise in key areas such as high-performance computing, data analytics, and advanced numerical simulations, all while learning to critically evaluate and interpret computational results in the context of their specific field. The programme stands at the intersection of traditional scientific disciplines and modern computing, giving students a competitive edge by integrating cutting-edge computational tools with scientific inquiry. By bridging the gap between computing and scientific research, graduates will be well-prepared to tackle some of the most challenging problems in fields such as physics, biology, engineering, environmental science, and beyond. Whether pursuing a career in industry or academia, this MSc opens doors to roles that require deep technical knowledge, innovative problem-solving skills, and the ability to manage and interpret large-scale data sets. This programme is suitable for students with motivated and inquisitive minds who have a background in science, engineering or a related subject, and a strong interest in computing. Some experience in programming is essential.

Normally a first-class Bachelors degree in science, engineering or a related subject and with a strong interest in computing or an overseas qualification of the equivalent standard. Students with a first degree in Finance, Management, Actuarial Science or related subjects will not normally be accepted.