Aalborg University invites applications for a Postdoctoral position in Probabilistic Machine Learning for Spatio-Temporal Data Modelling, based at the Department of Computer Science, Copenhagen Campus. The position starts 1 January 2026 (or soon thereafter) for 18 months, with a possible extension based on performance.
This position is part of the DK-Future project — Probabilistic Geospatial Machine Learning for Predicting Future Danish Land Use under Compound Climate Impacts — funded by the Villum Foundation (Synergy Programme). The postdoc will develop probabilistic spatio-temporal models, advancing Bayesian, ensemble, and diffusion approaches to forecast land-use change under climate uncertainty. Work will be supervised by Assoc. Prof. Andrés R. Masegosa and conducted in close collaboration with Prof. Jamal Jokar Arsanjani.
Qualifications: PhD in Machine Learning, AI, Computer Science, Statistics, or a related field. Experience in probabilistic/Bayesian methods, variational inference, spatio-temporal modelling, or deep learning (TensorFlow/PyTorch/JAX). Experience with geospatial or environmental data is a plus.
Location: Copenhagen, Denmark. Deadline: 21 November 2025. Employment: Full time. Ref. number: 2025/631.
More information and online application: https://www.vacancies.aau.dk/scientific-positions/show-vacancy/vacancyId/868169
