Some questions can't be answered in a lab. The system is too small, too large, too fast, or too complex to test directly. Computational scientists answer them anyway, by building mathematical models, writing the code to run them, and turning the results into insight that engineers and researchers can act on.

The programs in this webinar approach that work from different starting points. You can start at bachelor's level with a solid foundation in mathematics, computer science, and AI, then apply it to domains like biology, economics, or environmental science. You can specialise in simulating materials across every scale, using methods like finite element analysis, molecular dynamics, and machine learning, with a direct path into industrial R&D. You can use numerical simulation to solve problems in electrical engineering, mechanical engineering, and physics that experiments can't reach. Or you can bring your background in physics, chemistry, biology, or earth sciences and learn the computational tools to push research in your field further.

All programs presented are taught in English.

You will learn:

• What each direction involves day to day, from programming and simulation projects to research work and specialisation choices
• Which program fits your background, whether you are finishing school or already hold a degree in mathematics, computer science, engineering, or a natural science
• What you need to apply, including academic prerequisites, programming experience, language certificates, and deadlines
• Where graduates go: industrial R&D, engineering, data science, research institutes, and PhD programs
• Live Q&A with the program teams

Come with the problem you want to solve. Leave knowing where to learn how.