PhD and Postdoctoral Positions in Causal AI for Health and Life Sciences
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.