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Faculty of Physics and Astronomy :
Chair of Theoretical Physics / Computational Design of Functional Interfaces
In order to fill a fixed-term position in full-time (39.83 hours/week = 100%) at the earliest possible date, we are looking for 1
Postdoctoral Researcher (m/f/x) in Machine Learning for Light-Induced Excited-State Dynamics in Materials
The successful applicant will join the research group of Prof. Silvana Botti at the Research Center Future Energy Materials and Systems (RC FEMS) and the Ruhr University Bochum (RUB). The group develops first-principles and machine-learning methods to describe electronic excitations, light–matter interaction, and ultrafast dynamics in materials and at functional interfaces. The newly founded Research Center focuses on developing innovative materials and systems for sustainable energy applications. The center’s research areas include photovoltaics, thermoelectricity, energy storage, fuel cells, and sustainable chemical processes, among others. Its interdisciplinary approach involves collaborations between physicists, chemists, engineers, and material scientists to address the challenges of transitioning to a low-carbon economy. The center also offers opportunities for graduate students and postdoctoral researchers to participate in cutting-edge research projects and receive advanced training in the field of energy materials and systems. The chair of Prof. Botti is affiliated with the Faculty of Physics and Astronomy of the Ruhr University Bochum. This faculty is a leading research and teaching institution in the fields of experimental and theoretical physics and astronomy, with a focus on condensed matter physics, astrophysics, and particle physics.
We are seeking a highly motivated postdoctoral researcher (m/f/x) with a strong background in condensed matter physics and a proven record in developing machine-learning methods. The position focuses on the development of new computational approaches that combine real-time time-dependent density functional theory (rt-TDDFT), nonadiabatic excited-state dynamics, and machine learning, in order to reach the time and length scales needed to describe light-induced phenomena in complex materials.
Scope: full-time
Duration: fixed-term, 3 Years
Start: at the earliest possible date
Apply by: 2026-10-06
Your tasks:
The successful candidate (f/m/x) will
- develop and apply methods at the intersection of real-time TDDFT, nonadiabatic excited-state molecular dynamics, and machine learning
- design and implement machine-learning models for photo-excited systems (e.g., excited-state interatomic potentials, machine-learned Hamiltonians, models for the time evolution of electronic states), trained on and validated against first-principles data
- investigate ultrafast light-induced processes in materials, such as photoinduced structural phase transitions, coupled electron–phonon dynamics, and non-equilibrium carrier and lattice dynamics, including materials and interfaces relevant for energy applications
- publish results in peer-reviewed journals, present them at international conferences, and collaborate with theoretical and experimental partners within RC FEMS and beyond
Your profile:
Required qualifications:
- A PhD in condensed matter physics, or a very closely related field; candidates who have not yet completed their PhD may apply if the doctoral degree will be awarded by the date of signing the employment contract
- A strong background in physics
- Strong knowledge of quantum mechanics and of the theory of electronic excitations in materials
- Solid understanding of light–matter interaction and of first-principles methods for excited states and their dynamics (e.g., TDDFT, nonadiabatic molecular dynamics)
- High-level programming skills (e.g., Python, C/C++, Fortran) and experience with modern machine-learning frameworks (e.g., PyTorch)
- Demonstrated experience in the development of machine-learning methods and models for physical or materials problems. We are looking for researchers who develop methods, codes, and models — not users. Experience limited to running standard codes or training simple ML models will not be considered.
- Demonstrated ability to carry out independent research, evidenced by publications in peer-reviewed journals
- Good command of English, both written and spoken
Desirable qualifications:
- Experience with real-time TDDFT simulations of solids under laser excitation
- Experience with the development of machine-learning interatomic potentials or machine-learned electronic Hamiltonians, e.g., based on graph neural networks, and their extension to excited states
- Knowledge of electron–phonon coupling, nonadiabatic dynamics, and non-equilibrium phase transitions in photoexcited materials
- Experience with large-scale ab initio and machine-learning-driven molecular dynamics
- Experience with high-performance computing environments
- Experience in collaborating with experimental groups (e.g., ultrafast spectroscopy, time-resolved diffraction)
We offer:
Challenging and varied tasks with a high level of independence, Employment at one of the largest universities in Germany within the University Alliance Ruhr, Collaboration in a committed and appreciative team, Extensive training and professional development opportunities, A job in the heart of the lively Ruhr metropolitan region with its diverse cultural offerings
- A full-time postdoctoral position (TV-L E13, 100%)
- An interdisciplinary and international research environment
- Access to cutting-edge computational infrastructure (local GPU cluster, national and European HPC resources)
- Opportunities for professional development, including participation in international conferences and workshops
- A vibrant research campus with a broad spectrum of research activities in materials science, physics, and chemistry
- Ruhr-Universität Bochum is a family-friendly university
Further information:
The position is salaried and based on the collective agreement of the Länder (TV-L). If the personal and collective agreement requirements are met, the employee will receive pay grade A13 TV-L.
Further information can be found at (in German).
The place of work is Ruhr University Bochum.
If the position is funded by third-party funds the employee has no teaching obligation.
RUB sees itself as a university with an international presence. The campus languages are German and English. Competence in at least one of the two languages and the willingness to learn the other are a prerequisite. RUB provides corresponding free courses for employees.
German language courses are offered by the University Language Center (ZFA) in the field of German as a Foreign Language (DaF). https://www.daf.ruhr-uni-bochum.de/daf/mitarbeitende/index.html.en
The Staff Council has the right to participate in all selection interviews. At the request of a candidate (m/f/x), it will ensure its participation in the entire procedure. Please contact wpr@rub.de.
The Ruhr-Universität Bochum is one of Germany’s leading research universities, addressing the whole range of academic disciplines. A highly dynamic setting enables researchers and students to work across the traditional boundaries of academic subjects and faculties. To create knowledge networks within and beyond the university is Ruhr-Universität Bochum’s declared aim.
The Ruhr-Universität Bochum stands for diversity and equal opportunities. For this reason, we favour a working environment composed of heterogeneous teams, and seek to promote the careers of individuals who are underrepresented in our respective professional areas. The Ruhr-Universität Bochum expressly requests job applications from women. In areas in which they are underrepresented they will be given preference in the case of equivalent qualifications with male candidates. Applications from individuals with disabilities are most welcome.
Contact persons for further information:
Silvana Botti Tel.: +49 234 32 17776
Travel costs, accommodation costs and loss of earnings or other application costs for job interviews can unfortunately not be reimbursed.
We look forward to receiving your application via our online application portal by 2026-10-06. Please make sure to mention the reference number ANR 6138.
RUHR-UNIVERSITÄT BOCHUM
44801 Bochum
Universitätsstraße 150
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