Doctoral researcher on uncertainty and causality in climate models

About the role

The Centre for Logic and Philosophy of Science (CLPS) at KU Leuven invites applications for a four‑year full‑time PhD researcher position. The project, “From Data to Mechanisms: Classifying and Reducing Uncertainty in Climate Models,” explores how uncertainty and causality interact in climate science, especially when machine‑learning methods are used.

Key responsibilities

• Develop a refined typology of uncertainty in climate science.
• Adapt INUS‑based Coincidence Analysis for high‑dimensional climate datasets.
• Create physics‑informed, causally interpretable machine‑learning parametrisations for land‑atmosphere interactions.
• Synthesise findings into an epistemological framework linking uncertainty and causality.
• Collaborate with interdisciplinary teams and contribute to seminars and workshops.

Required profile

• Master’s degree in Philosophy, Earth/Environmental Science, Climatology, or a related discipline.
• Strong analytical abilities and experience in computational programming.
• Interest in philosophy of science (for science graduates) or background in physics, statistical modelling, data science, or machine learning (for philosophy graduates).
• Prior knowledge of climatology, weather, or climate modelling is a strong plus.
• Ability to work independently and good organisational skills.

Required skills

• Computational programming
• Statistical modelling
• Machine learning
• Climate modelling

What we offer

• Four‑year funded PhD position with supervision by Prof. Sylvia Wenmackers.
• Opportunity to work at the interface of philosophy, climate science, and advanced data analytics.
• Access to interdisciplinary research community and international workshops.