Fully Funded PhD Positions in Data Science, Machine Learning, and AI for Molecular Medicine, Geosciences, Energy, and Environmental Science Helmholtz International Berlin Research School in Data Science in Germany

HEIBRiDS (Helmholtz International Berlin Research School in Data Science) is offering fully funded PhD positions in Berlin, Germany, for interdisciplinary research at the intersection of data science, machine learning, deep learning, AI, statistical modelling, and mathematical modelling.

The call covers projects in Molecular Medicine, Materials & Energy, Earth & Environment, and Geosciences. One highlighted opportunity is co-supervised by Begüm Demir from BIFOLD, connecting AI methods with real-world scientific data. Research will be carried out at partner Helmholtz centers in the greater Berlin area, including GFZ, Helmholtz Zentrum Berlin, and Max Delbrück Center for Molecular Medicine, in collaboration with partner universities such as Technische Universität Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, and Charité.

The fellowship is 4 years long and funded at E13 TVöD/TV-L. The programme also offers dual supervision, training in ML and data science, conferences, networking, and international research stays. It is aimed at Master's graduates or soon-to-be graduates from computer science, engineering, mathematics, physics, statistics, or related fields.

The application call is open for the Spring 2026 cycle, and the deadline given in the post is 2026-06-24. Applicants should use the HEIBRiDS online application portal to submit their materials.