About our research
Research insitute
The Master’s programme in Computing Sciences is offered in close collaboration with the Institute for Computing and Information Sciences (ICIS), and more specifically the Data Science department. ICIS looks beyond its own field as it integrates the know-how with other disciplines such as law, medicine, and neuroscience. Through this approach, ICIS is relevant not only in research, but also tackles the challenges of IT in modern-day society.
Institute for Computing and Information Sciences (iCIS)
Research department
Our Data Science department has a strong international reputation in areas such as machine learning, probabilistic modelling, and information retrieval. Our ambition is to develop principled, theoretically sound approaches for the analysis of complex data. Our research is guided by real-world problems and data sets. We closely work together with the data owners, to turn their data and domain knowledge into novel insights and tools based on our software and algorithms.
Researchers
Get to know our researchers and their work, you could be working alongside them in this Master's!
Student projects
A large part of this programme is focused on research. As data questions play a role in many different research areas, you have a broad array of research groups to work with during your Master's. You can think of astronomy, particle physics, chemometrics, neuroscience, and bioinformatics. Examples of student projects are:
Fold2vec: protein structure embedding for deep learning
The structure of proteins to a large extent determines their function and activity in the cell. The recently introduced AlphaFold2 deep learning protein structure predictor led to a dramatic increase in the number and quality of available protein. This calls for novel methods to work with protein structures, particularly based on deep learning. In this project, we will explore the extension of a protein structure embedding method with the aim to (1) increase resolution, and (2) take uncertainties generated in protein structure predictions into account in structure-based deep learning.
Predicting/improving semiconductor production at NXP Nijmegen
The fabrication of semiconductors is complex and challenging, has long production lead times (up to 4 months), the production facility contains many very complex tools and during production a huge amount of data is generated. In our big data analytics journey so far, we have built a Big Data cluster (Hadoop) with over 400 billion production quality records. With these records we want to investigate if we can increase yield by adjusting production parameters.
Knowledge about past climate and extreme weather events is an essential part of understanding future climate change and variability. Paper archives are digitized by experienced typists at high costs or with citizen science projects that can take considerable time, but recent advances in AI/ML make the global data rescue community wonder if this process can be automated. This project will focus on improving Tabular Structure Recognition (TSR), which can help extract locations of cells and headings in photos of historical records. This project will be done in collaboration with KNMI (The Royal Netherlands Meteorological Institute).
Research projects
Curious what our researchers are working on? View our ongoing projects.
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AI and Simulations for Decoding the Spatiotemporal Dynamics of Immune Responses
Microscopes allow scientists to film cell movement. This project is working on developing AI to improve analysis of cell movement videos.
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Improved Pulse Program
In this project, researchers are working on the further development of Alliander's PULSE Program. Through this work, they are contributing to improving daily network management and making the power grid future-proof.
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What is the influence of cable temperature on the possible load of the electricity network?
What is the influence of temperature (think of heat pumps and airconditioning) on the possible load on the electricity network?
Research facilities
New Devices of the Future Lab
In our New Devices of the Future Lab, students and staff experiment with new devices such as smart glasses (e.g. Google glass), smart watches, brain computer interfaces, quadcopters and 3D printers. This lab provides ample opportunities for Data Science and AI students to analyse interesting, nontrivial sensor data.