Specialisations
Take a unique specialisation in Quantum Computing at Maastricht University
Quantum computing is a muchanticipated new technology that is still in its infancy. “As soon as quantum hardware becomes widely available, quantum computing has the potential to revolutionise research and technology”, says Georgios Stamoulis, assistant professor at the Department of Advanced Computing Sciences at Maastricht University. He will lecture about topics of Quantum Computing.
The specialisation in Quantum Computing…

As soon as quantum hardware becomes widely available, quantum computing has the potential to revolutionise research and technology
Curriculum (tentative)
As of the academic year 20232024, Maastricht University offers a specialisation in Quantum Computing. The specialisation is accessible for students of the master’s programmes in Artificial Intelligence and Data Science for Decision Making. During the last semester of the first year, you can opt to follow an introductory course. In year 2, you specialise further by taking more courses, and top it off with a research project on quantum computing.
If you complete the required courses and the corresponding research project, the specialisation in Quantum Computing will be listed on your master’s diploma. It’s also possible to follow some of the specialisation’s courses as electives.
 Year 1  Period 5: Introduction to Quantum Computing for AI & Data Science
 Year 2  Period 1: Quantum Algorithms
 Year 2  Period 2: Quantum Artificial Intelligence  Quantum Information & Security
Be prepared
As soon as the hardware becomes available, he says. So, why should we already study quantum computing now? “Well, we better be prepared”, Stamoulis answers. Quantum Delta NL, the Dutch quantum ecosystem, therefore started working with Dutch universities to begin educating specialists in quantum computing. The demand for specialists in this emerging field is already high. “Companies and research groups ask for it”, says Matúš Mihalák, programme director of the master’s studies that will embed the new specialisation programme. “They want someone in their team who can advise them on the possibilities of quantum computing. Just think of financial institutions that want to know about quantumproof encryption or scientists who research quantum computing.”
Linear algebra
The specialisation in Quantum Computing will introduce you to realistic as well as theoretical possibilities of quantum computing. The technology relies on the behaviour of the smallest particles that make up our world, as defined by the theory of quantum mechanics. Quantum mechanics is a linear theory described by linear algebra. “With quantum computing you can theoretically work on problems that fit into the mathematical structure of quantum mechanics”, states Stamoulis. “It will be our challenge to find linear problems, or parts of nonlinear problems, like curing cancer or solving the climate problem, that can be in reach of quantum computing technology.”
Examples
Most examples of potentially solvable problems are in the field of quantum mechanics itself, like in quantum chemistry. Another, notorious, case is cryptography using prime factorisation (describing a number as the product of two prime numbers). Quantum computers, when available, can heavily exploit prime factorisation, whereas classical computers have a very hard time finding the primes of large numbers efficiently. Don’t worry: the money in your bank account is safe for now. The current best experimental quantum computer can factor 21 into its primes 7 and 3 (using Shor's algorithm).
Courses
The specialisation in Quantum Computing is accessible to master’s students of the Artificial Intelligence and Data Science for Decision Making programmes. It offers four courses. You will familiarise yourself with designing quantum algorithms and see how you might use them in quantum artificial intelligence, machine learning, cryptology and security. You will do a project on quantum computing as well. It’s also possible to follow some of the specialisation’s courses as electives.
All pictures by IBM Research and are licensed under CC BYND 2.0.