Tommy Sonne Alstrøm

DTU Compute is offering a PhD scholarship in Causal-informed Machine Learning Methods for Climate Modelling as part of the newly started IcyAlert project. The project focuses on improving predictions of Arctic ice-free summers and their potential climate impacts at multi-seasonal time scales using global climate models , causal analysis , and machine learning . This makes the opportunity especially relevant for candidates interested in the intersection of computer science , environmental science , statistics , and climate research. The project is led by the Danish Meteorological Institute in partnership with the Royal Meteorological Institute of Belgium and the Technical University of Denmark . The post is associated with Tommy Sonne Alstrøm, Associate Professor at DTU, and mentions collaborators including Tian Tian, David Docquier, Stéphane Vannitsem, and Clara Edmonds. Funding: The IcyAlert project is funded by the Novo Nordisk Foundation (grant NNF25OC0097271). The post does not specify stipend amount, tuition coverage, or other financial details beyond the scholarship funding. Eligibility: The post does not list detailed entry requirements, but it is a PhD scholarship and therefore intended for applicants seeking doctoral study. Relevant background in machine learning, climate modelling, causal inference, or related quantitative fields would be a strong fit. Deadline: Application deadline is August 9th (normalized here as 2026-08-09). How to apply: Use the DTU recruitment portal linked in the post to view the vacancy and submit your application. Review the IcyAlert project page for more context on the research aims and consortium. Apply before the deadline.