PhD Student Positions in Data-Driven Materials Design at INM – Leibniz Institute for New Materials INM – Leibniz Institute for New Materials in Germany

The INM – Leibniz Institute for New Materials in Saarbrücken, Germany, is a globally recognized center for materials research, collaborating with national and international institutions and industry partners. The Data-Driven Materials Design group, led by Prof. Viktor Zaverkin, is recruiting several PhD students to join a vibrant interdisciplinary research environment that includes the INM, Saarland University’s Faculty of Mathematics and Computer Science, and the German Research Center for Artificial Intelligence (DFKI).

The group’s research focuses on developing machine learning methods for modelling molecules and materials, aiming to accurately predict their properties across various length and time scales. Projects may involve machine-learned interatomic potentials, atomistic foundation models, active learning strategies for efficient data generation, data-driven acceleration of atomistic simulations, and generative models for molecular and materials design. The exact research topic will be tailored to the candidate’s interests and expertise.

PhD students will conduct independent research, develop and implement novel machine learning methods, apply these methods to molecular and materials systems, contribute to scientific publications and conference presentations, and collaborate with researchers from materials science, chemistry, and machine learning. The group is embedded in an interdisciplinary environment combining experimental groups in materials science, chemistry, synthetic biology, biophysics, and machine learning.

Applicants should have a Master’s degree in computer science, applied mathematics, physics, chemistry, materials science, or a related field, with background in at least one of the following: machine learning, computational chemistry or materials science, atomistic simulations, or scientific computing. Experience in scientific programming (e.g., Python, PyTorch) is expected. Candidates should demonstrate interest in developing machine learning methods for modeling molecules and materials, ability to work independently and collaboratively, and excellent written and spoken English. The motivation letter should specify research interests.

The INM offers an interdisciplinary and international research environment, access to modern computational infrastructure, opportunities to publish in leading journals and present at international conferences, and a high degree of scientific freedom. Employment is according to the German public service salary scale, with benefits. The institute is an equal opportunity employer, promotes diversity, and encourages applications from women and people with disabilities.

Applications are accepted via the INM online portal and will be reviewed continuously until the positions are filled. Applicants should submit a motivation letter, CV, relevant certificates, and names of 1–2 references as a single PDF file (max. 10 MB).