A PhD position is available at the Institute for Materials Chemistry (Theoretical Chemistry) at TU Wien.

The PhD project is oriented towards the application and development of machine-learning methods for modelling complex oxides at the atomic scale. Special focus will be put on the use of neural networks for active learning and structure prediction.

Funding for this position comes from the Austrian Science Fund (FWF) in the framework of a recently approved SFB (DE: Spezialforschungsbereich, EN: collaborative research center): Taming Complexity in Materials Modeling, TACO. The first funding period comprises four years, and the project may be renewed for a further four years upon positive evaluation at the end of that period. The participants in the project are research groups in the areas of physics and chemistry from TU Wien and the University of Vienna. The objective of the project is the improvement of experimental and theoretical materials modelling, in particular with the help of machine learning. The focal point is the understanding of energy-relevant phenomena and processes at the atomic scale.

Admission requirements: Master's degree in chemistry, physics or materials science or an equivalent university degree from Austria or abroad.

Other knowledge: We expect excellent grades, good communication skills in English and an interest in learning or previous experience with modern programming languages like C++ or Python.

For further information on the project and the research group, please contact: [email protected] (https://www.imc.tuwien.ac.at/tc_madsen).

We offer a stimulating work environment in a cutting-edge research setting, a friendly work atmosphere and a high degree of independence The salary is commensurate with FWF guidelines for a doctoral candidate position https://www.fwf.ac.at/en/research-funding/personnel-costs (14 monthly salaries per year). The original appointment is for 3 years and can be prolonged.

We seek to fill the position as soon as possible.

If interested, please send your application as one pdf file to [email protected]. This should include a motivation letter and curriculum vitae (incl. evidence of desired qualifications), and contact addresses of up to 3 references.