RT @gerasimoss: Join us @OSCMaastricht for the inaugural FAIR Coffee Event! Discussing #OpenScience, becoming #FAIR and ☕ https://t.co/9Hnr…
Founded in 1992, DKE is a fast-growing department undertaking research to advance the fields of artificial intelligence, data science, computer science, applied mathematics and robotics. Furthermore, DKE maintains a large network of industry partners through the award-winning KE@Work programme and through our research collaborations.
The department provides education through one bachelor’s programme and two master’s programmes.
Research at the Department of Data Science and Knowledge Engineering spans the disciplines and interfaces of artificial intelligence, data science, computer science and applied mathematics.
We develop new tools and methodologies to advance these fields. At the same time, we collaborate with a wide range of institutes both within and outside of Maastricht University and work on diverse applications, including in the fields of health and medicine, logistics, biology, art, physics, cybersecurity, neuroscience and education.
A 3-year bachelor's programme offering a unique combination of artificial intelligence, computer science and mathematics.
A 2-year master's programme with a focus on simulating human intelligence for a wide variety of applications: from game design to patient diagnosis.
A 2-year master's programme with a focus on extracting valuable information from large datasets for widespread applications such as: scheduling customer service agents and optimising supply chains or modelling biological processes.
We also offer an exchange programme for students looking to study abroad.
Mathematics in Maastricht? Why yes – for more than 30 years already! The recently-established Mathematics Centre Maastricht (MCM) is a first, however, and has already seen over fifty researchers from across the university join its ranks.
In 2016 Marta Dávila Mateu, now a graduate of Data Science and Knowledge Engineering, moved to Maastricht, a city completely unknown to her. Her choice turned out to be a double-edged sword. She found the lack of skate culture depressing, but enjoyed her studies, especially the focus on the mathematics behind data.