Fully Funded PhD Positions in Machine Learning & AI for Science

Develop foundational machine learning—spanning geometric deep learning, generative flow matching, and foundation models—to decode, model, and program biological systems at Europe’s newest AI-native research institute.

Core ML Research Directions
PhD researchers focus on principled ML methodology with publications at top venues (NeurIPS, ICML, ICLR):
• Geometric Deep Learning & Equivariance: Symmetry-aware representations, invariant architectures, and neural differential equations over non-Euclidean manifolds and 3D molecular structures (SE(3)SE(3)SE(3)).
• Generative Modeling & Continuous Dynamics: Flow matching, continuous-time diffusion, and optimal transport for macromolecular design and complex cellular trajectories.
• Relational Foundation Models & Graph ML: Theoretical expressiveness and generalization of GNNs, graph transformers, and large-scale relational foundation models.

Mentorship & Faculty
Work with leading ML faculty led by Michael Bronstein (Scientific Director for AI; ELLIS Fellow; Oxford) alongside PIs with research backgrounds from Mila, MIT, Oxford, Caltech, and EPFL.

Compute & Research Environment
• Large-Scale Compute & Frontier AI Stack: Dedicated next-generation GPU cluster providing unconstrained compute for large-scale training, paired with direct access to a wide variety of state-of-the-art closed and open-weight LLMs / foundation models.
• Collaborative AI-for-Science Wet Lab: Work hand-in-hand with in-house experimentalists and robotic automation facilities to rapidly validate model predictions and generate high-throughput data in a true closed-loop setup.
• Academic Ecosystem: Strong partnerships with TU Wien, University of Vienna, CeMM, and international research hubs.

Key Information
• Contract: 4 years, fully funded (competitive salary + Austrian social benefits)
• Degree Track: PhD in Computer Science / Machine Learning awarded by TU Wien or University of Vienna
• Location: Vienna, Austria (consistently ranked the world’s most livable city)
• Start Date: 1 September 2027
• Application Deadline: 1 November 2026

We value diverse perspectives, intellectual curiosity, and a strong commitment to interdisciplinary collaboration across computational and life sciences. We warmly welcome applicants of all backgrounds and nationalities.

Explore research groups & apply: https://phd.aithyra.at/