Working within a large EU project, the candidate will do research leading to a PhD thesis with a focus on the role of climate change on recent extreme weather events. During the last years, many extreme weather events in Europe and worldwide have occurred, causing damage to infrastructure and casualties. This has raised the question about the role of climate change in altering the odds or the magnitude of a number of these extremes. While it is clear that climate change in general intensifies heat waves and extreme rainfall events, there are many unanswered questions with respect to the role of internal climate variability and feedback processes that are important for extremes. Moreover, to what extend climate change affects the socio-economic impacts from extremes (e.g., drought-related harvest losses or flood damage) remains largely unexplored. Recently developed methods in artificial intelligence provide enormous potential to fill this research gap.
The candidate will become part of the Climate Extremes research group (climateextremes.eu) within the Institute for Environmental Studies (IVM). Together with colleagues at IVM, the Netherlands Royal Meteorological Institute (KNMI) and partners abroad, the candidate will work on applying novel machine learning methods on massive climate data sets (both from observations and climate models) to better understand the dynamical processes and feedbacks leading to extremes. This will provide essential information to quantify the respective role of climate change versus that of natural cycles on the occurrence of specific events. The candidate is expected to write peer-reviewed papers as partial fulfilment of the PhD thesis, to participate in international conferences and regular project workshops, and to assist in some limited teaching activities.
This research is part of a large EU-funded project, XAIDA (Extreme Events: Artificial Intelligence for Detection and Attribution). The work will be carried out at the IVM at VU Amsterdam, and the candidate will work in close collaboration with our consortium partners, including KNMI, Climate Informatics Group (DLR, Germany), LSCE/IPSL (Paris) and ETH (Zurich). XAIDA brings together the expertise of a research consortium of 15 universities and research institutes, uniting experts in climate modeling, machine learning and statistics. Together they will design new methods and apply them to recent high-impact events to examine links to climate change and predict if the occurrence of such events, or even more-intense ones, will increase in the future. They will foster dialogue with concerned stakeholders (e.g. insurance companies) to prepare risk assessment and adaptation for similar future events, as well as develop material for teachers, for the education of younger generations.
Your duties
- Analyzing large observational and climate model data sets
- Applying machine learning methods (like causal discovery and interpretable AI) to these datasets to understand drivers behind heatwaves and droughts in Europe and the larger Mediterranean area
- Writing a PhD thesis consisting of 4 scientific papers
- Working with colleagues of the project consortium and contributing to project reporting
- Assisting in some limited teaching activities at IVM