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This project combines first-principles simulations based on density functional theory DFT with the development of automated and reusable computational workflows for muon studies in materials.

The goal of the project is to develop and apply advanced first-principles methodologies to determine muon stopping sites and muon-induced effects in materials, explicitly accounting for the quantum nature of the muon. Building on state-of-the-art DFT workflows for such simulations, you will extend existing approaches beyond classical treatments, incorporating quantum effects and modern data-driven techniques.

Starting with DFT-based calculations of muon stopping sites and migration pathways, including nudged elastic band NEB calculations, you will explore quantum treatments of the muon using approaches such as path-integral molecular dynamics PIMD and/or the stochastic self-consistent harmonic approximation SSCHA. You will further investigate the use of machine-learned interatomic potentials MLIPs to efficiently capture muon–material interactions and enable simulations at an affordable computational cost. Depending on interests and project evolution, you may also explore generative AI approaches to predict favorable muon stopping sites. We do not expect candidates to be experts in all these techniques at the start of the PhD; training and learning will be an integral part of the project.

A key component of the project is also the translation of these methods into robust, reusable, and user-friendly workflows, enabling their adoption by the broader µSR and materials-science communities. This includes contributing to and extending existing AiiDA-based workflows and graphical interfaces (e.g. AiiDAlab Quantum ESPRESSO applications) for automated muon simulations and analysis.

Your profile

We are looking for a highly motivated candidate with background in computational materials science or condensed-matter physics, and a keen interest in developing and applying advanced simulation methods and implementing them in workflows. You have experience working independently but also enjoy working in an interdisciplinary and collaborative environment and are eager to combine methodological development with real scientific applications.

Requirements for candidates include:

Master’s degree (or close to completion) in physics, materials science, chemistry, engineering, or a closely related field
Hands-on experience using density functional theory DFT for research or projects
Working knowledge of Python for scientific computing and data analysis
Comfortable communicating research ideas and results in English, both in writing and in conversation
Interest in quantum simulations, materials modeling, and/or developing new computational methods

You will be based at the Paul Scherrer Institute PSI in the "Materials Software and Data" group of Dr Giovanni Pizzi, and work in close collaboration with Prof. Dr Titus Neupert at University of Zürich UZH, and Prof. Dr Nicola Spaldin at ETH Zürich where you will be enrolled in the doctoral program in Materials Science. The doctoral studies include coursework at ETH Zürich and may involve teaching duties. Results obtained during the PhD are expected to be published in peer-reviewed journals and presented at international conferences.

We are convinced that our research team functions best when it is maximally diverse, and we particularly encourage applications from members of under-represented groups.

We offer

Our institution is based on an interdisciplinary, innovative and dynamic collaboration. You will profit from a systematic training on the job, in addition to personal development possibilities and our pronounced vocational training culture. If you wish to optimally combine work and family life or other personal interests, we are able to support you with our modern employment conditions and the on-site infrastructure.

For further information, please contact Dr Giovanni Pizzi, e-mail [email protected].

Please submit your application online by 14 June 2026 including a one-page cover letter summarizing your interest in the position and how your background prepares you for this role, your CV, transcript of records, and contact details for two referees for the position as a PhD Student in Quantum-Mechanical Simulations of Muons in Materials (Index-Nr. 7301-07).

Paul Scherrer Institute, Human Resources Management, Serdal Varol, 5232 Villigen PSI, Switzerland

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