Kjell Jorner

Kjell Jorner is an Assistant Professor of Digital Chemistry in the Institute for Chemical and Bioengineering at ETH Zurich's Department of Chemistry and Applied Biosciences. His research group focuses on integrating computational methods and machine learning to address challenges in chemical synthesis, materials design, and reaction prediction.

Education:

• PhD from Uppsala University (Photochemistry of aromatic compounds)
• Postdoctoral studies at AstraZeneca UK (Reaction prediction using computational chemistry and ML)
• Postdoctoral studies at University of Toronto (Molecular design of catalysts and organic electronic materials)

Research Interests:

Professor Jorner's work bridges computational chemistry, machine learning, and experimental design. Key areas include:

• Development of quantum mechanics-machine learning hybrid approaches for reaction feasibility prediction
• Inverse molecular design of functional materials (e.g., singlet-fission systems)
• Computational catalyst optimization and high-throughput screening methods
• Digital tools for chemical education and cheminformatics

Publication Trends (2023-2025): Recent articles demonstrate a strong focus on machine learning applications in chemistry, including reaction prediction algorithms, catalyst design frameworks, and automated molecular generation. A recurring theme is the development of computational tools to accelerate materials discovery and optimize chemical processes.

Laboratory & Team: Leads the Digital Chemistry research group at ETH Zurich (HCI E 137) exploring computational approaches to chemical challenges.