I study the way ice sheets respond to climate change, both in the (distant) past and in the future. I do this using ice-sheet models: computer programs that calculate how much snow falls and melts each year, how much this causes the ice sheet to grow or shrink, and how the ice deforms under its own weight. My research focuses on the interactions between the ice sheet and the rest of the Earth system: when the ice sheet melts, how does this affect the local climate? What's the influence of the melt water on ocean currents? How does the Earth's crust deform under the changing weight of the ice? And in what clever ways can I build these processes into my computer model, so that it's accurate enough to provide useful conclusions, but still fast enough to be able to simulate periods of hundreds of thousands of years?

I also specialise in the development of these kinds of computer models. These days, models like this consist of tens of thousands, sometimes even hundreds of thousands of lines o code, which makes it more and more complicated for researchers to work with these digital tools. For how do you construct such a program in such a way that the enormous pile of code remains coherent and understandable? How do you set it up so that multiple programmers can work on it together without getting in each other's way? And how do you prevent yourself, while being hired as a climate scientist, to slowly turn into a full-time programmer? New insights from the field of information technology can help with this. I make sure the ice & climate research group keeps up to date with these new developments, so that we can continue to work effectively with our digital tools.