Open Positions

1

Time Span

as soon as possible for 3 years

Application Deadline

02 Mar 2026

Financing

yes

Areas of study

Mathematics, Applied Mathematics, Technomathematics, Applied Computer Science, Data Science, Computer Science, Artificial Intelligence, Theoretical Chemistry, Physics

Description

The University of Wuppertal (Germany) invites applications for a PhD position (Research Assistant) in the group of Prof. Peter Zaspel, starting March 1, 2026. The position is part of the DFG Priority Programme “Molecular Machine Learning” and embedded in the research project “Multi-fidelity, active learning strategies for exciton transfer in cryptophyte antenna complexes”. The PhD project involves interdisciplinary research at the interface of computer science and mathematics, with a focus on bivariate molecular machine learning for modeling molecular interactions and properties.

Research tasks
The successful candidate will work on interdisciplinary research at the interface of computer science and mathematics with applications in molecular machine learning. A central aspect of the position is the development of novel machine learning methods for modeling molecular properties, in particular regression models for bi-molecular properties. The research is embedded in the thematic context of multi-fidelity and active learning strategies for molecular systems.

The candidate will collaborate in an international research team on related research questions in machine learning, uncertainty quantification, and high-performance computing, with applications in the natural and engineering sciences. The position also includes teaching responsibilities equivalent to 4 contact hours per week, as well as supervision of student research and thesis projects.

Required qualifications
Applicants must hold a completed Master’s degree (or equivalent) in a relevant discipline such as computer science, mathematics, physics, or data science. They should have strong analytical skills in the context of machine learning and/or numerical mathematics, as well as an excellent command of a programming language, preferably Python or C/C++.

The candidate should have an interest in developing novel bivariate methods in machine learning for molecular property prediction within an interdisciplinary application. Ideally, applicants have experience with multipole methods, low-rank approximations, or tensor methods. A good command of English, the working language within the team, is required. We are looking for a competent, proactive personality with commitment and motivation, the ability to work independently, and enjoyment of teaching.

As part of the application process, candidates are required to complete a scientific programming task within the thematic context of the advertised position: https://www.hpc.uni-wuppertal.de/de/peter-zaspel/challenge-in-bi-molecular-machine-learning/

Employment conditions
This is a qualification position in the sense of the German Academic Fixed-Term Contract Act (WissZeitVG) and serves to support a doctoral program. The position is full-time (part-time employment is possible), initially limited to up to three years, with the possibility of extension for the completion of the doctorate within the legal framework. The salary is paid according to TV-L E13.

Application
The application deadline is March 2, 2026. Applications must include a motivation letter, CV, proof of successful graduation, relevant certificates or references, and (if available) a Bachelor’s or Master’s thesis, as well as the completed scientific programming task. Applications are submitted via the University of Wuppertal’s online application portal https://stellenausschreibungen.uni-wuppertal.de under reference number 25353.

For further information, please contact
Prof. Dr. Peter Zaspel
zaspel@uni-wuppertal.de