PhD Position in Computational Electron Microscopy
The Technische Universität Berlin is seeking a highly motivated Research Assistant to join the Emmy Noether Independent Junior Research Group led by Dr. Laura Niermann.
This position offers an exciting opportunity to develop advanced physics-based algorithms for reconstructing strain and electric fields at interfaces of nano-heterostructures, with the opportunity to pursue a doctorate.
About the Research Group
The research group focuses on the numerical inversion of dynamical electron diffraction, working at the interdisciplinary intersection of theory and experiment, scanning transmission electron microscopy (S/TEM), and materials science.
Key Responsibilities
You will contribute to the development and application of innovative computational and experimental methods in electron microscopy.
- Develop experimental measurement methods for acquiring dynamical electron diffraction datasets, including 4D-STEM and electron holographic beam tilt series.
- Simulate and analyse dynamical diffraction effects.
- Optimise, evaluate and validate numerical inversion approaches, particularly algorithms and regularisation methods.
- Apply reconstruction methods to semiconductor heterostructures and domain walls in ferroelectrics.
- Acquire and analyse complementary datasets using NBED, Differential Phase Contrast (DPC) and Off-Axis Electron Holography.
- Explore machine learning approaches for advanced reconstruction methods.
- Collaborate with national and international partners in computational electron microscopy and materials science.
Access to state-of-the-art 300 kV S/TEM infrastructure
Benefit from direct access to highly specialised transmission electron microscopy facilities at Technische Universität Berlin for your experimental research.
Candidate Profile
The ideal candidate should have:
- A completed Master’s degree, Diplom or equivalent in Physics or a related discipline, by the start of employment.
- Very good knowledge of numerical programming, computational modelling and experimental data analysis.
- Experience in software development and programming, ideally in Python.
- Independence, self-motivation and preferably experience in independent scientific research.
- Good knowledge of German and/or English.
- Experience with numerical libraries and machine learning frameworks such as PyTorch or JAX is desirable.
- Experience in S/TEM, solid-state physics, statistical methods or machine learning is an advantage.
Position Details
Take the next step in your research career
Submit your application, quoting reference number II-423/26, together with the usual application documents in a single file (maximum 5 MB).
APPLY BY EMAIL →Contact: Dr. Laura Niermann
Application deadline: 03 December 2026
Faculty II – Mathematics and Natural Sciences
Institute of Physics and Astronomy · Technische Universität Berlin