Prospective Master and Bachelor students

We are always interested in hearing from prospective Bachelor and Master students who would like to join us for research internships or thesis work. Our group has supervised Master students in Data Science, Artificial Intelligence, and Medical Biology; two of these then went on to join our group as PhD students.

PhD candidates and postdocs

PhD position: Simulating large T cell collectives

Closing date: February 28th, 2021

We are looking for a PhD Candidate who is curious about building a large-scale simulation of the human immune system and using it to improve our knowledge about how the real immune system learns. When you hear about 'artificial intelligence', you might think of computer programs or systems that are modelled after the brain - the biological system that is most commonly associated with the term 'intelligence'. But our bodies harbour a second intelligent system that is just as critical for our ability to thrive in this world: the adaptive immune system. And while the brain has been very much at the centre of attention in computer science in recent years, fuelled by the rise of 'artificial networks', there remain vast expanses of unexplored territory when it comes to understanding the immune system from a computational perspective. The Computational Immunology research group is looking for a PhD candidate to join the quest for building an 'artificial immune system': a computer simulation of how the T-cells that make up a large part of that system, process and store information, make decisions, learn, get confused, and forget.

Artificial immune systems have a long history dating back to the late 1980s, but for several years, only relatively small systems have been built. Like artificial neural networks in their early days, these early artificial immune systems were not very successful at reproducing biological phenomena or solving machine learning tasks. Over several years, our group has developed new algorithms that allow us to scale up such artificial immune systems by several orders of magnitude, which finally makes it possible to build simulations that resemble the real system in terms of size and complexity. You will further develop these new tools and build large-scale simulation models that can process real data on how the immune system responds to external stimuli (such as a virus infection) and make predictions that can be tested by comparing them with experimental data. Through iterations between model predictions and experiments (which are performed by our collaborators), you will harness your models to generate insight into the underlying principles of information processing and learning in the immune system. For an example of how this works, please have a look at our recent paper.

Ultimately, you will use your simulation to try and predict immune responses against specific foreign stimuli, such as a specific protein sequence (comparable to, for instance, a piece of the SARS-COV2 spike protein). If such predictions were possible, even if only in part, they would greatly improve our ability to design safe vaccines and other immunotherapeutic treatments rapidly. They would also help us understand how a patient's exposure to past pathogens might affect their responses to other pathogens in the future.

Of course, you will not work towards these goals on your own. Within our group, this position is part of a larger project, funded by a Vidi grant from the Dutch Research Council (NWO), and is part of a broader research line that also includes a new project funded by the Human Frontiers Science Program (G7 nations). The Computational Immunology group is affiliated with both Radboud University (Data Science section) and the Radboud university medical center (Tumor Immunology Department). Within our NWO and HFSP projects, we also collaborate closely with Dr Judith Mandl's group at McGill University, Montreal, with whom we regularly exchange students and staff. In summary, we provide ample opportunity for working with and learning from world-class scientists in both data science and immunology.

Are you curious about this position and do you want to learn more about employment conditions, the Data Science group, or working at the Radboud University? Please use this link to get to the official vacancy posting a the RU website.