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

• MSc degree in climate physics, earth sciences, physics, or similar (preferably with demonstrable affinity with machine learning or Big Data) or an MSc degree in computational sciences or similar (preferably with demonstrable affinity to climate sciences)
• Good skills in programming and using large datasets (preferably in Python, or willing to learn Python). Experience with High Performance Computing (or interest in learning) is desirable
• Familiar with or willing to learn Machine Learning techniques.
• Strong quantitative methodological skills
• Good communication skills, since the work involves collaboration in a larger team of international and multi-disciplinary researchers and stakeholders

Fixed-term contract: 4 years.

A challenging position in a socially involved organization. The salary will be in accordance with university regulations for academic personnel and amounts €2,325 (PhD) per month during the first year and increases to €2,972 (PhD) per month during the fourth year, based on a full-time employment. The job profile: is based on the university job ranking system and is vacant for at least 0.8 FTE.

The appointment will initially be for 1 year. After a satisfactory evaluation of the initial appointment, the contract will be extended for a duration of 4 years.
Additionally, Vrije Universiteit Amsterdam offers excellent fringe benefits and various schemes and regulations to promote a good work/life balance, such as:

• a maximum of 41 days of annual leave based on full-time employment
• 8% holiday allowance and 8.3% end-of-year bonus
• solid pension scheme (ABP)
• contribution to commuting expenses
• optional model for designing a personalized benefits package

The ambition of Vrije Universiteit Amsterdam is clear: to contribute to a better world through outstanding education and ground-breaking research. We strive to be a university where personal development and commitment to society play a leading role. A university where people from different disciplines and backgrounds collaborate to achieve innovations and to generate new knowledge. Our teaching and research encompass the entire spectrum of academic endeavor – from the humanities, the social sciences and the natural sciences through to the life sciences and the medical sciences.

Vrije Universiteit Amsterdam is home to more than 26,000 students. We employ over 4,600 individuals. The VU campus is easily accessible and located in the heart of Amsterdam’s Zuidas district, a truly inspiring environment for teaching and research.

Diversity
We are an inclusive university community. Diversity is one of our most important values. We believe that engaging in international activities and welcoming students and staff from a wide variety of backgrounds enhances the quality of our education and research. We are always looking for people who can enrich our world with their own unique perspectives and experiences.

The Faculty of Science
The Faculty of Science inspires researchers and students to find sustainable solutions for complex societal issues. From forest fires to big data, from obesity to medicines and from molecules to the moon: our teaching and research programmes cover the full spectrum of the natural sciences. We share knowledge and experience with leading research institutes and industries, both here in the Netherlands and abroad.

Working at the Faculty of Science means working with students, PhD candidates and researchers, all with a clear focus on their field and a broad view of the world. We employ more than 1,250 staff members, and we are home to around 6,000 students.
 
About the department
The department of Water and Climate Risk is a dynamic group of 45 international researchers, faculty members and PhD students within the Institute for Environmental Studies (IVM). Explicit attention is given to the interaction between the hydrological and climate systems, and how these interactions lead to risk to society, the economy, and the environment. The focus is on water and climate extremes such as floods and droughts, to estimate impacts from these extremes on various economic sectors, and to examine which strategies can be developed to reduce impacts and risk. This requires the mapping of climate and water-related hazards, as well as the exposure of people and assets and their vulnerability, and estimating associated costs to reduce risk. Risk management and risk transfer strategies are evaluated in the context of both developed and developing countries. Model simulations, data processing, data assimilation and the integration of economic instruments, such as insurance, are key scientific strengths of the department.
Within WCR, the Climate Extremes group led by Dr Coumou studies links between climate change and extreme weather with a special focus on how dynamical changes (i.e. to jetstreams, storm tracks or Hadley circulation) can change the frequency or intensity of extremes. The group pioneered the use of machine-learning techniques, including causal discovery and interpretable AI, to understand atmospheric teleconnections behind extreme weather events. The team’s mission is to (1) understand the processes behind extreme weather, (2) assess the role of climate change on current and future extremes, (3) quantify the impacts and risks for society, in particular for agriculture and food security, and (4) improve seasonal to sub-seasonal (S2S) forecasting. The team unites expertise on novel data-driven methods (causal discovery, dynamical systems analyses) with state-of-the-art climate models. We have active on-going collaborations with research institutes and stakeholder worldwide. For more information see our website: climateextremes.eu