The Digital Chemistry Laboratory is led by Prof. Dr. Kjell Jorner at the Institute of Chemical and Bioengineering, within the Department of Chemistry and Applied Biosciences at ETH Zurich and associated with the ETH AI Center. We are an interdisciplinary group at the intersection of chemistry and computer science. Our mission is to accelerate chemical discovery using digital tools. We predict chemical reactivity and molecular properties using machine learning, artificial intelligence, computational chemistry, and cheminformatics. Our ultimate goal is the computer-aided design of molecules and catalysts.

Cycloaddition reactions are among the most valuable synthetic tools for building molecular complexity, as they can form ring systems with high atom economy, contributing to innovations in, e.g., materials science and pharmaceuticals. Recently, energy transfer photocatalysis (EnT) has emerged as a ground-breaking method for facilitating cycloadditions. However, the reactivity and selectivity of substrates in EnT-catalyzed reactions remain challenging to predict, given the limited mechanistic understanding and scarcity of experimental data. 

This project aims to systematically address these challenges by building chemistry-informed machine learning models for selectivity and reactivity prediction. These models will also provide valuable mechanistic insights that enable the generalization of selectivity trends across diverse reaction conditions and substrates. We will also turn the models into user-friendly tools that will equip synthetic chemists with a robust predictive framework that enables precise prediction of reaction outcomes. 

The project is part of an international collaboration with the German Priority Program on the “Utilization and Development of Machine Learning for Molecular Applications – Molecular Machine Learning” (SPP 2363) and will involve tight collaboration with the group of Prof. Dr. Frank Glorius from the University of Münster, world-leading experts in photocatalysis and molecular machine learning. This collaboration will involve using the models in synthetic method development carried out in the Glorius group, including the selection of further reactions to run, and their application to targets of medicinal interest.

As a PhD student in our growing team, you will develop machine learning methods to predict the reactivity and selectivity of energy-transfer-catalyzed photocycloaddition reactions. You will furthermore identify descriptors for photochemical reactions that can be used by the models to generalize better to new substrates and reaction types. You will be expected to collaborate closely with our experimental partners in the group of Prof. Dr. Glorius. Further responsibilities include contributing to the teaching activities of our department.

We are looking for a committed and motivated candidate that is excited to push the boundaries of research in digital chemistry. 

Essential experience, skills, and characteristics:

• A master’s degree in either chemistry, chemical engineering, computational science, materials science, physics, or related fields, or expectation of obtaining such a degree before the expected starting date of September 1
• English proficiency
• Self-motivation, ability to work independently and solution-oriented mentality
• Interdisciplinary and collaborative mindset and desire to work with people from different disciplines and backgrounds
• Programming experience using languages such as Julia, Python, R, etc.

At least one of the following:

• Experience in applying machine learning from research projects or thesis
• Experience in quantum-chemical simulations from research projects or thesis

Desirable but not necessary criteria:

• Experience in organic synthesis from research projects or thesis

You will join a dynamic, and growing research group in the emerging field of Digital Chemistry and in the highly motivating environment of ETH Zurich. We foster a modern and supportive group culture and value diversity, independence, and initiative. The position is embedded in an exciting and interdisciplinary research environment with connections to the ETH AI Center and the National Centre of Competence in Research (NCCR) Catalysis, connecting the chemical sciences, digitalization, and sustainability.

A competitive salary is paid according to Rate 2 of the Doctoral student salary ladder.

In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish.

We look forward to receiving your online application until May 31, including:

• Cover letter
• Curriculum vitae
• Copies of BSc and MSc educational records

Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.

Further information about the group can be found on our website . Questions regarding the position should be directed to Prof. Dr. Kjell Jorner by email at [email protected]. Any applications that come in via email will be disregarded.

ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.