PhD position in large-scale GPU-based training in molecular machine learning

Are you interested in developing new machine learning training methods for large to huge data sets and have strong programming skills ideally on GPUs, then apply for our just opened PhD position!

A PhD position is available in the team of Prof. Peter Zaspel at University of Wuppertal, Germany. The position is focused on the development of novel machine learning training algorithms on GPUs in context of molecular simulations for materials design under the project “Multi-fidelity methods for fast large-scale mixed-precision molecular machine learning on GPUs”. The respective research will involve the further development of large-scale machine learning models and hardware-aware algorithms in an interdisciplinary application.

The team of Prof. Peter Zaspel is located at Bergische Universität Wuppertal. The international team focuses on machine learning, uncertainty quantification and high performance computing in context of applications from the natural sciences, engineering and beyond. It is embedded in the research group on Scientific Computing and High Performance Computing. For more details, see and

A successful applicant is expected to have a Master’s degree (or equivalent) in computer science, mathematics, physics, data science or similar discipline, strong analytical skills in context of machine learning and/or (numerical) mathematics, excellent proficiency in a programming language (preferable Python or C/C++) and interest in developing novel, hardware-aware training methods on GPUs in context of kernel-based / Gaussian Process machine learning for simulation applications. Experience in hardware-aware programming on GPUs or parallelization of algorithms is an advantage. A good command of English is essential, both as the local working language and because of our international collaborations. We look for a competent personality with initiative and commitment, who has the ability to work independently and who enjoys teaching (support).

We offer a 3 year PhD position. The salary will be paid in accordance with the Collective Agreement for the Public Service of the Federation (Tarifvertrag des öffentlichen Dienstes, TVöD Bund), with salary level 13 (75%). The position has teaching (support) duties. The place of employment will be Wuppertal, Germany.

The position is available immediately and applications will be considered until February 12, 2024. In order to apply, please submit a letter of motivation, a CV, copies of transcripts and optionally a copy of your MSc thesis (all as one PDF). If you you would like to apply or have questions on the position please contact Prof. Peter Zaspel via zaspel(at)

Neuer Experte will innovative Forschungs-Software entwickeln

Peter Zaspel ist neuer Professor für Software für datenintensive Anwendungen an der Bergischen Universität Wuppertal.

Forschende in Wissenschaft und Technik arbeiten mit großen Datenmengen. Diese beinhalten Messungen, Simulationen und Kombinationen hiervon, wofür eine umfangreiche IT-Infrastruktur nötig ist. Die Entwicklung von effizienter und erweiterbarer Software sowie von Methoden für datenintensive Anwendungen in den Naturwissenschaften, der Technik und darüber hinaus ist das Ziel der Forschungsarbeit von Peter Zaspel. Anwendungsfelder solcher Programme können zum Beispiel Quantenchemie, Klimarekonstruktion und Medikamentenforschung sein.

Please find the full press release here.

Research Project on Machine Learning for Molecular Systems

Priority Programs of the German Research Foundation (DFG) are intended to provide tangible impetus for the further development of science in important topics. Two researchers from Jacobs University Bremen are involved in a newly launched program on machine learning for molecular systems in physics and chemistry: Peter Zaspel, Professor of Computer Science, and Ulrich Kleinekathöfer, Professor of Theoretical Physics. This also gives them access to a nationwide network of experts for topical exchange.

Please find the full press release here.

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Find the full press release here.

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Find the full press release here.