PhD in Ultra-Fast Machine-Learning Interatomic Potentials for Nanoindentation of TiC Materials Luxembourg Institute of Science and Technology in Luxembourg

The Luxembourg Institute of Science and Technology (LIST) is offering a fully funded PhD position focused on the development and application of ultra-fast machine-learning interatomic potentials (UFPs) for nanoindentation studies of titanium carbide (TiC) materials. This research opportunity is based in Belvaux, Luxembourg, and involves a temporary contract spanning 14 + 22 + 14 months, with a competitive salary, health insurance, generous paid leave, and additional benefits such as flexible working hours and lunch vouchers.

The successful candidate will join a dynamic, multicultural research environment and work under the supervision of Dr. Matthias Rupp. The project centers on data-driven atomistic simulations, specifically leveraging UFPs for large-scale molecular dynamics (MD) simulations of TiC and related materials. Titanium carbides are renowned for their exceptional hardness, high melting point, and resistance to wear and abrasion, making them critical for industrial applications such as hard alloys, ceramic-metal composites, protective coatings, and aerospace turbines.

The PhD research will involve modeling the mechanical properties and plastic deformation of Ti-C materials with diverse compositions and structures. Key tasks include conducting MD-based nanoindentation simulations, analyzing defects, and further developing machine-learning potentials both methodologically and in implementation. The goal is to push the boundaries of UFPs to simulate mechanical properties in agreement with and beyond experimental results.

Applicants must hold a master’s degree in computational materials science or a closely related discipline. Essential skills include knowledge of materials theory, experience with computational methods, familiarity with machine-learning interatomic potentials, and proficiency in Python programming. Fluency in English and a collaborative, proactive attitude are required. Additional desirable qualifications include experience developing machine-learning interatomic potentials, working with UFPs, molecular dynamics (ideally using LAMMPS), and contributing to public code repositories.

PhD enrollment will be at the University of Luxembourg, Belval campus. Please note that university enrollment fees (currently 400 EUR per semester) must be covered by the successful applicant, and the master diploma must be recognized in Luxembourg. For details on diploma recognition, refer to the University of Luxembourg and government websites provided.

LIST offers a stimulating research environment with innovative infrastructures, personalized learning programs, and a commitment to diversity and inclusion. The institute encourages curiosity, innovation, and entrepreneurship, and supports the professional development of its staff.

Applications are accepted online only via the HR system. Required documents include a motivation letter, scientific CV, list of publications/patents, and contact details of two references. Applications will be continuously reviewed until the position is filled, with selection based on alignment of skills and expertise with project requirements.

For further information, visit the LIST website or contact Dr. Matthias Rupp. Apply now to join a leading research institute and contribute to cutting-edge materials science using advanced machine-learning techniques.