PhD student in Spatio-Temporal Machine Learning at Linköping University

Want to push the boundaries of AI while working on problems that actually matter? Linköping University is looking for a PhD student to develop cutting-edge machine learning methods for spatio-temporal data, focusing on generative modelling, data assimilation, and multi-scale neural networks, with real-world applications in urban gas dispersion, air quality, and climate science.

You'll be based at the Division of Statistics and Machine Learning, supervised by Prof. Fredrik Lindsten, and collaborate closely with climate scientists at Lund University. Linköping University is one of Sweden's top AI institutions with a thriving AI ecosystem, being the host organization for the WASP program (https://wasp-sweden.org/) - a major national research program in AI, autonomous systems and software - as well as the AI Factory MIMER and the upcoming EuroHPC Arrhenius.