**Open minded** We are a young, innovative university located in the heart of the Ruhr metropolis. We pride ourselves in outstanding research and teaching, think in terms of opportunities rather than limitations and develop ideas with a view to the future. Diversity is an integral part of our culture as we promote potential and are committed to upholding genuine equity in education. **Location** Duisburg **Application area** Faculty of Physics, Theoretical Physics Scientific Researcher in Theoretical Physics (f/m/d, Nr. 117-26) **salary group 13 TV-L** We are seeking PhD candidate(s) to join a newly established research group and develop a multiscale Virtual Material Design (VMD) pipeline for neuromorphic spintronics based on topological spin textures (TST) — e.g. 2D skyrmions and 3D hopfions. 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. **Start of employment** as soon as possible **Duration of employment** 4 years **Working time** 29 h 52 min (75%) **Your main tasks** 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. As part of the position, opportunities for further scientific qualification are offered. **Your profile** - 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 you** - a varied, diverse range of tasks in a research-intensive environment with international exchange - a pleasant working atmosphere in a dynamic team - 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 **Application deadline** 2026-04-15 **Code number** 117-26 **Application** Please send your application, quoting the reference number **117-26** to Dr. Juba Bouaziz, e-Mail: [j.bouaziz@fz-juelich.de ](mailto:j.bouaziz@fz-juelich.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 two 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 **Information about the job** You can find information about the faculty at: [https://www.uni-due.de/physik/index\_en.php](https://www.uni-due.de/physik/index_en.php) **Learn more** University of Duisburg-Essen pursues the goal of promoting the diversity of its members. [www.uni-due.de/diversity/en](https://www.uni-due.de/diversity/en) In accordance with the State Equal Opportunities Act, women with the same qualifications are given preferential consideration. Applications from suitable disabled persons and persons of equal status within the meaning of § 2 para. 3 SGB IX are desired. By applying for one of the advertised positions, you expressly agree to the requirements in accordance with the General Data Protection Regulation and to being contacted by mail. Further information on data protection can be found [**here**](https://www.uni-due.de/imperia/md/content/dokumente/2023/ude-datenschutz-bewerber-innen.pdf).
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