PhD and Postdoctoral Positions in Causal AI for Health and Life Sciences RWTH Aachen University in United Kingdom

RWTH Aachen University is recruiting for Causal AI for Health, a research group led by Prof. Dr. Adèle Helena Ribeiro in the area of Explainable AI in Life Sciences. The post announces one postdoctoral researcher (2 years) and one PhD student (3 years), both funded at 100% TV-L E13.

The research focus is at the intersection of causal discovery and inference, Bayesian and probabilistic machine learning, uncertainty quantification, integration of expert knowledge, multimodal data modeling, and causal abstraction and representation learning. The group aims to build causal frameworks that work robustly on large-scale biomedical datasets and address challenges such as data heterogeneity, latent confounding, selection bias, and distributional shifts.

Applications are especially relevant for students and researchers interested in computer science, statistics, mathematics, and biomedical data science. The project page describes broader applications in public health, clinical research, malaria, mental health, cardiovascular diseases, long COVID, and cancer.

Eligibility highlights: a strong background in mathematics, computer science, or a related field is expected; experience in the listed methods is a plus. The positions are research-focused and suitable for candidates motivated to contribute to causal and explainable AI for the life sciences.

How to apply: send a CV, two references, and a research statement (up to two pages) describing your background, interests, prior contributions, motivation, and goals. Email the application to [email protected] and use the correct subject line for either the PhD or postdoctoral track. Review begins on 2026-05-04, and later applications may still be considered.