Postdoc on Causal Machine Learning for Spatio-temporal Datasets Leiden University in Netherlands

Leiden University’s Leiden Institute of Advanced Computer Science (LIACS) is offering a full-time postdoctoral position in causal machine learning for spatio-temporal datasets. The project focuses on developing advanced algorithmic methods for the automatic and scalable assessment of interventions in observational spatio-temporal data. The research sits at the intersection of machine learning, causality, and algorithm design, with applications such as reducing methane emissions, understanding public health interventions, and analyzing complex processes observed through IoT sensors, mobile devices, and Earth observations.

The postdoc will be embedded in LIACS’s Spatio-temporal Data Analysis and Reasoning (STAR) and Automated Design of Algorithms (ADA) research groups, with additional collaboration opportunities across the institute and internationally. The position also includes collaboration with Dr. Elena Raponi and Dr. Saber Salehkaleybar, and participation in the teaching activities of the STAR Research Group, including supervision of BSc and MSc students.

The appointment is for 2.5 years, initially for one year and extendable by another 1.5 years after positive evaluation. It is partially funded by the Dutch Research Council (NWO) through the Aspasia premium awarded to Dr. Mitra Baratchi. The salary is stated as €3,546 to €5,538 gross per month for a full-time appointment, with standard Dutch university employment benefits including holiday allowance, end-of-year bonus, pension scheme, commuting reimbursement, flexible working, and hybrid working within the Netherlands.

Applicants should have, or be close to obtaining, a PhD in Computer Science, Artificial Intelligence, or a closely related field. Strong expertise in one or more of the following is expected: machine learning for spatio-temporal data, causal machine learning (causal discovery and causal inference), and automated machine learning. The call also emphasizes a strong publication record, collaborative skills, solid programming ability in Python or another programming language, and excellent English communication skills.

Applications must be submitted online before 30 September 2026. Required documents include a cover letter, a brief research plan describing a research idea and research questions, an academic CV, PhD thesis, links to key publications, and the names and addresses of two referees.

This is an excellent opportunity for a researcher interested in causal inference, machine learning, and scalable methods for spatio-temporal data within a highly regarded computer science environment at Leiden University.