PhD Candidate or Postdoctoral Fellow in AI-Augmented Target Discovery for Translational Kidney Disease Helmholtz Munich in Germany

Helmholtz Munich is recruiting two outstanding researchers for a project on AI-augmented target discovery in translational kidney disease. The opening is for PhD candidates and/or postdoctoral fellows to join the group of Fabian Theis at Helmholtz Munich, in collaboration with Novartis Biomedical Research.

The project focuses on building next-generation AI models that can predict the effects of interventions in tissues, not just cell lines. The research combines foundation models for biology, perturbation prediction, intervention design, representation learning across modalities, causal and mechanistic modeling, and the development of “world models” for cellular and tissue systems. A major goal is to translate models across organoids, experimental systems, and patient samples to identify interventions that move cells from disease toward health.

The collaboration is generating large-scale perturbation datasets across organoid systems, patient samples, and experimental models to better understand kidney disease mechanisms and discover therapeutic targets. The post is especially relevant for candidates interested in AI for biology, computational biology, machine learning, computer science, physics, mathematics, or related quantitative fields.

Eligibility highlights: you do not need to be a kidney expert. Strong candidates may come from AI/ML, computer science, physics, mathematics, computational biology, or related disciplines. The announcement does not mention a deadline, stipend amount, or tuition details in the provided text.

How to apply: use the official job posting link to access the Helmholtz Munich application page and follow the instructions there. The post also links to a news article describing the Helmholtz Munich–Novartis collaboration for additional context.