Grossunternehmen |
2000 Angestellte (Schweiz) |
| Temporaire: Oui | Taux: 100% |
| Villigen | Langue:en |
| Site internet |
The Paul Scherrer Institute PSI is the largest research institute for natural and engineering sciences within
Switzerland. We perform cutting-edge research in the fields of future technologies, energy and climate, health
innovation and fundamentals of nature. By performing fundamental and applied research, we work on sustainable solutions
for major challenges facing society, science and economy. PSI is committed to the training of future generations.
Therefore, about one quarter of our staff are post-docs, post-graduates or apprentices. Altogether, PSI employs 2300
people.
Become part of Muoniverse This position is part of Muoniverse, a Swiss National Centre of Competence in Research
(NCCR) dedicated to advancing muon science across particle physics, quantum materials, and applications ranging from
energy research to cultural heritage.
Muoniverse brings together 30 research teams from universities, research institutions, and museums in a highly
collaborative network, supported by the Muoniverse Research School, which coordinates training, exchanges, and career
development for PhD students and postdocs.
Learn more at:
Who we are looking for Muoniverse positions often serve as bridges between individual research groups and
institutions, supported through dedicated measures. We are seeking candidates who thrive in such collaborative
environments, enjoy connecting people and ideas across disciplines, and are comfortable working within networked
structures. Your ability to contribute to a culture of openness and shared progress is as important as your technical
expertise.
Muoniverse is committed to promoting equal opportunities and diversity in science. It actively works towards a diverse
scientific community and an inclusive work environment.
For the new NCCR Muoniverse, in the Materials Software and Data Group we are looking for a
PhD Student in Quantum-Mechanical Simulations of Muons in Materials
Your tasksThis 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 ( AiiDAlab Quantum ESPRESSO applications) for
automated muon simulations and analysis.
Your profileWe 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 communica j4id10218797x j4it0521x j4iy26x