Postdoc position in reactive machine learning potentials
vor 1 Woche
ETH Zürich is well known for its excellent education, ground-breaking fundamental research and for implementing its results directly into practice.
About the PositionThe 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.
Project BackgroundMachine learning potentials (MLPs) that predict the energy of molecules or materials from their three-dimensional atomic coordinates are increasingly replacing quantum-chemical simulations in high-throughput screening and dynamical simulations. Trained on large amounts of chemical data, such MLPs can serve as “foundation models” that are broadly applicable across chemical and configurational space. While significant progress has been made in developing MLPs for equilibrium structures, they have been less successful for chemical reactions, for which much less data is available. While efforts are underway for data collection and training of reactive MLPs, another approach is to augment the architecture of the MLPs to better accommodate reactive events. In this project, we will develop and validate such MLPs that borrow elements from classical reactive force fields. These reactive MLPs target a broader generalization performance and will require much less training data. Finally, we will employ the developed MLPs for reaction prediction in important reaction classes.
As a postdoc in our growing team, you will develop and validate machine learning potentials based on reaction data. You will also work with and adapt classical reactive force fields for integration into the MLPs. Finally, you will validate the methods on important chemical reactions. Besides your own main project focus, you will contribute to the supervision of PhD and undergraduate students in the group.
ProfileWe 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 PhD in either chemistry, chemical engineering, computational science, materials science, physics, or related fields, or expectation of obtaining such a degree before February 2025
- 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.
- Experience of machine learning potential development
- Experience of classical force field development
- Experience of reaction simulations
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 the ETH standard. The initial contract duration is for one year, with the possibility of extensions up to three years.
Application ProcessWe look forward to receiving your online application until December 6, including:
- Curriculum vitae with publication list
- PhD degree certificate (if already available)
Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered. We will continuously evaluate applications as they come in.
Further InformationQuestions regarding the position should be directed to Prof. Dr. Kjell Jorner by email at kjell.jorner@chem.ethz.ch. Any applications that come in via email will be disregarded.
Further information about the group can be found on our website and you can follow us on X/Twitter at @DCL_ETHZ.
Job DetailsTitle: Postdoc position in reactive machine learning potentials
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