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In order to fill a fixed-term position in part-time (26,6861 hours/week = 67%) at the earliest possible date, we are looking for a

Doctoral Researcher (m/f/x) in Time-Resolved Vibrational Spectroscopy, Schienbein group, Theoretical Chemistry II, Research Alliance Ruhr

The research group of Dr. Philipp Schienbein (https://schienbein.eu) at the Chair of Theoretical Chemistry II at Ruhr-Universität Bochum (RUB) is part of the Research Center Chemical Sciences and Sustainability of the Research Alliance Ruhr (RAR). The RAR is a joint initiative of TU Dortmund, Ruhr-Universität Bochum and Universität Duisburg-Essen funded by the state of North Rhine-Westphalia to expand the research landscape in the metropolitan area Ruhr. Our group is located close to the RUB-Campus in Bochum. Our group focuses on the quantitative calculation and interpretation of (time-dependent) vibrational spectra of complex condensed-phase systems from first principles, with the aim of relating spectroscopic fingerprints to underlying molecular structure and dynamics, including systems driven out of equilibrium. To this end, we develop and apply ab initio molecular dynamics, non-linear and time-resolved spectroscopic formalisms as well as machine-learning approaches, with particular emphasis on aqueous and catalytic interfaces in explicit solvent and at finite temperatures.

Scope: part-time
Duration: fixed-term, 3 years
Start: at the earliest possible date
Apply by: 2026-06-04

Your tasks:

We are seeking a highly motivated doctoral student to work in the field of thermal and electrochemical oxidation catalysis. The project focuses on investigating catalytically relevant metal oxide systems using fully atomistic machine learning molecular dynamics simulations in explicit solvation. You will calculate quantitative, time-resolved IR and Raman spectra of these systems, enabling direct comparison with experimental measurements. Your work will involve identifying spectral fingerprints of catalytic reactions under realistic conditions, leading to an in-depth atomistic understanding of reaction mechanisms at metal oxide interfaces.

To achieve this, you will develop and parameterize machine learning models for vibrational spectra calculations. This includes generating training data using electronic structure methods and atomistic simulations. The project also has a strong methodological component, including contributions to the development of our in-house code Mimyria (https://github.com/pschienbein/mimyria) for machine-learning-accelerated vibrational spectroscopy.

The successful candidate is expected to present results at international conferences, publish in peer-reviewed journals, and actively participate in national and international collaborations within the research group.

Your profile:

Bachelors degree in chemistry, physics, materials science or a related field. At the start for your employment, we need a proof of your successfully completed Master/Diploma Degree in a similar field. Very good communication skills in English (equal to B2 or better, oral and writing) are essential. The ideal candidate will have some knowledge about electronic structure calculations (preferably density functional theory), atomistic simulation techniques like molecular dynamics or Monte Carlo, and programming skills in Python and/or C++. Experience in machine learning is desirable but not essential.

https://jobs.ruhr-uni-bochum.de/jobposting/e1cc9f3fdfecb1ca3cddce377fd1b5d1689198c40?ref=AfA