Understanding the magnetism in nanoparticles is an urgent issue in condensed matter physics and material science with impact on a manifold of applications, ranging from medicine to spintronic. Recent investigations indicate that common particle properties such as size and shape do not strongly correlate with the measured magnetic properties. This suggests other structural motives are responsible, for which a quantitative description does not presently exist. Your task will be:
- Investigate how internal strain arising from either the surface or internal defect structures can affect the global magnetic anisotropy
- Develop a fully atomistic description of a magnetic particle, in terms of both atomic positions and spin, that can quantitatively describe the relevant low-energy magnetic configurations
- Apply magnetic energy landscape exploration algorithms to determine barrier energies between such configurations, to make quantitative predictions as a function of temperature, of magnetic particle switching rates
- You hold a Master degree in Physics or Materials Science with an emphasis on Computational Science
- Spoken and written English on at least an upper-intermediate level (CEFR B2) is required
- Good knowledge of condensed matter physics, magnetism, and atomistic simulation methods, as well as programming skills for methodology development are required. You have strong interpersonal skills and a capability to work both in a team and independently
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 Prof Dr Peter Derlet, e-mail email@example.com, phone +41 56 310 31 64.
Please submit your application online by 31 January 2021 (including addresses of referees) for the position as a PhD student (index no. 4801-00).
Paul Scherrer Institut Human Resources Management, Melina Spycher, 5232 Villigen PSI, Switzerland, www.psi.ch