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A PhD position in Machine Learning is available in the group of Prof. Peter Zaspel at Jacobs University Bremen, Germany. The position is focused on the development of novel machine learning algorithms in context of molecular simulations for materials design. It is specifically embedded into the Priority Program SPP 2363 “Utilization and Development of Machine Learning for Molecular Applications – Molecular Machine Learning” funded by the German Research Foundation (DFG). The respective research will involve the further development of machine learning models and algorithms in an interdisciplinary application.

The group of Prof. Peter Zaspel is located at Jacobs University Bremen, a private, state-accredited, English-language research university. The research group focuses on machine learning, uncertainty quantification and high performance computing in context of applications from the natural sciences, engineering and beyond. For more details, see https://www.peter-zaspel.de/

This project is in close collaboration with the group of Prof. Ulrich Kleinekathöfer from the Physics Department at Jacobs University Bremen, whose group will contribute the materials design application (http://ukleinekat.user.jacobs-university.de/).

A successful applicant is expected to have a Master’s degree in computer science, physics, mathematics, data science or similar discipline, strong analytical skills in context of machine learning and/or (computational) physics / (numerical) mathematics, excellent proficiency in a programming language (preferable Python or C/C++) and interest in developing novel machine learning methodologies for simulation applications. Experience in (numerical) simulation is an advantage. A good command of English is essential, both as the local working language and because of our international collaborations.

We offer a 3 year PhD position. It is funded under the DFG grant “Multi-fidelity, Active Learning Strategies for Exciton Transfer Among Adsorbed Molecules”. 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 (100%). The place of employment will be Bremen, Germany.

The position is available immediately and applications will be considered until the position is filled. Applicants should submit a letter of motivation, a CV, copies of transcripts and optionally a copy of their MSc thesis together with the names of two referees by e-mail to Prof. Peter Zaspel at p.zaspel(at)jacobs-university.de

A PhD position in Machine Learning or Applied Mathematics is available in the group of Prof. Peter Zaspel at Jacobs University Bremen, Germany. The position is focused on the development of novel machine learning techniques in context of a large- to extreme-scale biochemistry simulation for photosynthesis (https://doi.org/10.1016/j.cell.2019.10.021). The respective research will involve the further development of kernel-based machine learning models (Kernel Ridge Regression, Gaussian Process Regression, etc.) towards multi-fidelity models and large-scale computations in an interdisciplinary application.

The group of Prof. Peter Zaspel is located at Jacobs University Bremen, a private, state-accredited, English-language research university. The research group focuses on machine learning, uncertainty quantification and high performance computing in context of applications from the natural sciences, engineering and beyond. For more details, see https://www.peter-zaspel.de/

This project is in close collaboration with the group of Prof. Ulrich Kleinekathöfer from the Physics Department at Jacobs University Bremen, whose group will contribute the biophysics simulation application (http://ukleinekat.user.jacobs-university.de/).

A successful applicant is expected to have a Master’s degree in computer science, (applied) mathematics 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 large-scale machine learning and computing applications. Experience in (numerical) simulation is an advantage. A good command of English is essential, both as the local working language and because of our international collaborations.

We offer a PhD position that is limited to 3 years. It is funded under the DFG grant “Excitation Energy Transfer in a Photosynthetic System with more than 100 Million Atoms”. 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 (100%). The place of employment will be Bremen, Germany.

The position is available immediately and applications will be considered until the position is filled. Applicants should submit a CV, a brief statement of research interests, a copy of their MSc thesis, and the names of two referees by e-mail to Prof. Peter Zaspel at p.zaspel(at)jacobs-university.de