PhD position in digital ligand engineering for nanocatalysis

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.

Metal and metal oxide clusters and nanoparticles are potent catalysts for many chemical reactions. Their structure and properties can be modulated by organic ligands, that exert influence by both steric and electronic properties. The choice and design of organic ligands therefore offers a promising avenue for fine control of both structure and the reactivity of nanocatalysts through ligand engineering. In this project, we will develop structure-activity relationships and computational ligand engineering algorithms for nanoparticle and nanocluster catalysis, leveraging state-of-the-art methodology from both the heterogeneous and homogeneous catalysis fields. This will include density functional theory simulations, reactive machine learning potentials, descriptor machine learning, generative models, and Bayesian optimization. The project is part of the DAEMON COST Action on Data-driven applications towards the engineering of functional materials and involves secondments to our collaborators at the University of Turku in Finland and TU Delft in the Netherlands. Furthermore, the project is coordinated with experimental partners at ETH Zurich and the University of Basel to leverage the developed algorithms in real-world catalysis applications.

As a PhD student in our growing team, you will work with computational chemistry methods to simulate the catalytic activity of cluster and nanoparticle catalysts. You will furthermore develop structure-reactivity relationships and multi-objective ligand design models. For experimental realization, you will use reaction optimization algorithms together with our partners to optimize catalyst activity. You will further contribute to the teaching activities of the group.

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. Preferentially before April 2025
• 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.

Desirable criteria:

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

You will join a new, dynamic, and growing research group in the emerging field of Digital Chemistry at 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 Competence Center for 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.