The position is embedded in the Emmy Noether Independent Junior Research Group led by Dr. Laura Niermann. The group focuses on the numerical inversion of dynamical electron diffraction and works at the interdisciplinary bridge between theory and experiment, as well as between (scanning) transmission electron microscopy (S/TEM) and materials science.

You will contribute to the development of physics-based algorithms for the reconstruction of three-dimensional strain fields in nano-heterostructures. The focus is on the numerical inversion of dynamical electron diffraction. For your experimental work, you will have direct access to the highly specialized, state-of-the-art 300kV S/TEM infrastructure at Technische Universität Berlin.

Your tasks will include:

• Development of experimental measurement methods for acquiring dynamical electron diffraction datasets, for example using 4D-STEM or electron holographic beam tilt series
• Simulation and analysis of dynamical diffraction effects
• Optimization, evaluation, and validation of numerical inversion approaches, especially regarding algorithms and regularization methods
• Application of the developed inversion methods to nanostructures (such as core-shell nanoparticles and semiconductor nanowires)
• Acquisition and analysis of comparison datasets using Nano-Beam Electron Diffraction (NBED), as well as HAADF and EDX tomography
• Exploration of machine learning approaches for the reconstruction
• Independent collaboration with national and international project partners in the fields of computational electron microscopy and materials science

A doctoral thesis (PhD) resulting from this work is possible. For further information, please contact Dr. Laura Niermann (laura.niermann@tu-berlin.de).

• Successfully completed university degree (Master, Diplom, or equivalent) in physics or a related discipline; or completion by the start of the employment contract
• Excellent knowledge of numerical programming, computational modeling, and data analysis
• Experience in software development and programming (ideally in Python)
• High degree of independence, self-motivation, and enthusiasm for scientific work desirable
• Good knowledge of German and/or English required; willingness to acquire the respective missing language skills
• Experience working with numerical libraries and machine learning frameworks (like PyTorch or JAX) desirable
• Experience in (scanning) transmission electron microscopy and/or solid-state physics desirable
• Knowledge of statistical methods as well as basic knowledge of machine learning desirable

Please send your application with the reference number and the usual documents (one file max. 5 MB) only via email to laura.niermann@tu-berlin.de.

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To ensure equal opportunities between women and men, applications by women with the required qualifications are explicitly desired. Qualified individuals with disabilities will be favored. The TU Berlin values the diversity of its members and is committed to the goals of equal opportunities. Applications from people of all nationalities and with a migration background are very welcome.