Doctoral researcher on uncertainty and causality in climate models
The Centre for Logic and Philosophy of Science (CLPS) at KU Leuven is seeking a PhD researcher in Philosophy of Science for a four-year full-time project on uncertainty and causality in climate models.
The successful candidate will join the project
From Data to Mechanisms: Classifying and Reducing Uncertainty in Climate Models
, funded by the KU Leuven Research Council and supervised by Prof. Sylvia Wenmackers and Prof. Nicole Van Lipzig. The research is based at the Institute of Philosophy, KU Leuven, within an active interdisciplinary centre that works on logic, philosophy of science, and the philosophies of the particular sciences.
The project investigates how uncertainty in climate science can be classified, estimated, and reduced, and how advanced mathematical models relate to causal mechanisms in climate phenomena. A key theme is the growing use of machine learning in climate modelling: while ML can improve predictive accuracy, it may also create black-box models that obscure causal structure and make uncertainty harder to interpret. The work therefore combines philosophical analysis with hands-on climate modelling.
The research programme includes four connected strands: developing a refined typology of uncertainty in climate science; adapting causation-tracking methods such as INUS-based Coincidence Analysis for high-dimensional climate data; designing physics-informed and causally interpretable machine-learning parametrisations for land–atmosphere interactions; and synthesising these results into an epistemological framework for understanding uncertainty and causality in scientific models. The project has relevance for climate policy, climate modelling, and other fields where machine learning is increasingly used.
Applicants should hold a Master’s degree in Philosophy, Earth or Environmental Science, Climatology, or a related discipline such as Geography, Geology, Engineering, Bio-engineering, Meteorology, Oceanography, Mathematics, Physics, or Informatics. Philosophy graduates should also bring skills in physics, statistical modelling, data science, or machine learning. Science or engineering graduates should have a strong interest in Philosophy of Science and be prepared to take additional philosophy courses as part of the doctoral programme. Prior knowledge of climatology, weather, or climate modelling is a strong advantage.
The position requires some experience in computational programming, strong analytical ability, independent working habits, good organisational skills, and the capacity to collaborate in an interdisciplinary environment. Excellent written and spoken English is required, and Dutch is considered an asset. The successful candidate must enroll in the doctoral programme of the Institute of Philosophy and take on some teaching-related duties. Candidates must not previously have held the status of doctoral grantee.
The offer includes a scholarship contract for one year, renewable up to four years after positive evaluation, together with benefits such as health insurance, access to university infrastructure, and sports facilities. The expected start date is from 1 October 2026 at the earliest, to be arranged with the candidate. Applications are reviewed immediately and suitable candidates may be invited before the formal deadline of 31 August 2026.
