Fully Funded PhD and Postdoctoral Openings in AI, Quantum Computing, Materials, and Biomedical Engineering at ETH Zurich ETH Zurich in Switzerland

ETH Zurich is advertising multiple fully funded PhD and postdoctoral opportunities across several research areas, including artificial intelligence, multimodal reasoning for oncology, quantum computing and optimization, machine perfusion platforms for organ and tissue culture, stone conservation materials science, and atomic-scale structure–function relationships in separation materials.

The postdoctoral opening in multimodal reasoning models for oncology is embedded in a collaboration between ETH Zurich, Kaiko.ai, and clinical partners. The project focuses on foundation-model style AI for oncology, including multimodal language models, tool-augmented inference, multi-agent workflows, process supervision, verifier-guided training, reinforcement learning-based post-training, calibration, uncertainty-aware outputs, and clinically grounded evaluation. This role is aimed at candidates with a PhD in AI/ML, medical AI, biomedical informatics, computational biology, or a related field.

The PhD on Quantum Computing × AI for Optimization is a joint ETH Zurich and IBM Research Zurich opportunity. It sits at the intersection of quantum computing, machine learning, and combinatorial optimization, with research directions such as AI-assisted quantum circuit design, discovery of quantum optimization algorithms, and quantum samples for classical AI solvers. Applicants should have a relevant Master’s degree and strong coding and theoretical/computational interests.

The PhD position on engineering of machine perfusion platforms for organ and tissue culture is hosted by the Macromolecular Engineering Laboratory of Prof. Mark W. Tibbitt at ETH Zurich. The project involves engineering ex situ organ perfusion systems, improving control software and sensor integration, and prototyping next-generation perfusion platforms for new biological applications. The role is especially relevant for students with backgrounds in mechanical, electrical, biomedical, or process engineering, robotics, or related fields.

The PhD opening in material science of stone conservation is part of a collaborative project on spatially graded 3D printing to study contour scaling in building stones. The student will use 3D-printed stone-like materials, perform laboratory weathering and testing, and help develop rapid on-site detection methods. A Master’s degree in conservation science, materials science, chemistry, chemical engineering, civil engineering, or conservation architecture is preferred, with strong experimental skills and good English.

The PhD position on Atomic-Scale Structure–Function Relationships in Separation Materials for Sustainable Processes is funded by the NCCR Separations and carried out under the co-supervision of Dr. Paula Abdala and Prof. Christoph R. Müller at ETH Zurich. The project studies CO₂ capture and critical element recovery using synthesis, advanced spectroscopy, X-ray absorption spectroscopy, pair distribution function analysis, and vibrational spectroscopy to connect atomic structure with separation performance.

Across the advertised roles, ETH Zurich emphasizes strong academic preparation, motivation, independence, teamwork, and the ability to work in interdisciplinary environments. Some positions require specific technical skills such as Python and ML frameworks, electromechanical design, embedded systems, materials synthesis, spectroscopy, or experimental lab work. The application process is centralized through ETH Zurich’s online portal, and applicants are asked to submit documents such as CVs, transcripts, motivation letters or research statements, and references. For the oncology postdoc, the application window is stated as one month until July 19.