2026-03-22 | PhD
Lab/Company : University of Duisburg-Essen
Location : Duisburg, Germany
Yearly income :
https://www.uni-due.de/karriere/stelle.php?kennziffer=117-26
Expiration : 2026-04-15 [YYYY-MM-DD]
The Faculty of Physics at the University of Duisburg-Essen is inviting applications for a PhD position to join a newly established research group and develop a multiscale Virtual Material Design (VMD) pipeline for neuromorphic spintronics based on topological spin textures, including 2D skyrmions and 3D hopfions. Project background: Topological spin textures (TSTs) combine topological stability, nanoscale size and fast nonlinear dynamics, making them promising building blocks for spintronic neurons, synapses and reservoir-computing elements. This project will systematically scan targeted quantum-material families where relativistic effects and competing magnetic interactions favour TST formation (magnetic 2D materials such as VSe₂, ternary rare-earth intermetallics like GdFe₂Si₂, and magnetic Weyl semimetals). Work is computationally driven and focuses on linking quantum calculations to reduced, physics-aware spin models so that materials can be ranked and engineered for device-relevant properties such as thermal stability, controlled stochasticity, switching dynamics and compatibility with neuromorphic architectures. The goal is to build and validate an automated multiscale workflow that maps first-principles electronic-structure data onto predictive atomistic spin-Hamiltonians and device-scale dynamical models. The candidate will run high-throughput, relativistic DFT calculations using all-electron codes (juKKR, FLEUR) on HPC platforms, manage and store data with AiiDA, and extract magnetic interaction parameters for coarse-grained spin models. To replace ad-hoc fitting, we will apply machine learning — in particular physics-constrained symbolic regression — to discover compact analytical spin-Hamiltonians and their parameter dependencies. These Hamiltonians will feed large-scale atomistic spin simulations to evaluate energetics, thermal stability, non-linear dynamics and stochastic response, and to propose materials engineering routes (composition, doping or strain) that optimise TST properties for neuromorphic computing. The outcome is a validated VMD pipeline that identifies candidate materials and provides concrete, model-based prescriptions for tuning their behaviour for spintronic neurons, synapses and reservoir computing. The duties include teaching obligations amounting to 3 hours per week. Qualifications: - We welcome applications from highly qualified and motivated individuals holding a Master of Science degree in condensed matter physics or materials science, with a focus on numerical simulations - Prior experience with theoretical and or computational project work is important - Prior experience with density functional theory or machine learning is desirable - Proficiency in the Python programming language is important, as well as Fortran - Strong written and oral communication skills in English are necessary - The ability to work independently and collaborate effectively with both theoretical and experimental partners is essential We offer: - A varied, diverse range of tasks in a research-intensive environment with international exchange - The opportunity to do a doctorate (PhD) at the Faculty of Physics - Family friendliness through childcare services and counselling for family care responsibilities - A wide range of further training programmes - Excellent public transport connections and free parking spaces - Attractive sports and health programmes (university sports) - The opportunity to work partly from home Start date: as soon as possible | Duration: 4 years | Workload: 75% (29h 52min/week) Application deadline: 15 April 2026| Reference number: 117-26 Please send your application quoting the reference number 117-26 to Dr. Juba Bouaziz, E-Mail: j.bouaziz@fz-juelich.de ; juba.bouaziz@uni-due.de Your application should contain: - A cover letter outlining your motivation for pursuing this position and how it aligns with your long-term career goals - A short description of your previous research work (max 2 pages) - A curriculum vitae (CV) - Two reference letters from individuals familiar with your work to be sent to the email address below - A copy of your Master thesis (if available) and transcript of records This position is also advertised on the University of Duisburg-Essen careers page: https://www.uni-due.de/karriere/stelle.php?kennziffer=117-26 You can find information about the Faculty of Physics at https://www.uni-due.de/physik/index_en.php

