Research assistant (postdoc) (f/m/d) (883)
Department: Department of Mathematics and Computer Science
Contribution to research on the integration of machine learning into quantum chemical methods and molecular simulation. A particular focus will be on the development, application, and evaluation of modern machine-learning methods for quantum chemical problems and molecular simulations, with a specific emphasis on research into variational quantum Monte Carlo methods for molecular simulation using neural-network-based ansatzes.
The position will play a central role in the maintenance, further development, and documentation of the DeepQMC software and the associated development and simulation infrastructure. This includes the implementation and evaluation of new methods, the further development of existing functionalities, and ensuring sustainable and reproducible software development.
In addition, the position will involve the academic supervision of doctoral researchers and MSc students, as well as the development of independent scientific research questions and new project ideas. The employee will contribute to scientific publications, conference presentations, and third-party funding proposals, and will participate in national and international collaborations as well as other scientific activities of the research group.
The position includes teaching duties in accordance with the applicable regulations governing teaching obligations. The position is intended to support the individual's own academic qualification (habilitation).
Key Requirements
Completed university degree (Master's or equivalent) and PhD in mathematics, computer science, physics, or a related discipline.
- At least four years of full-time professional experience in academic research, as well as evidence of relevant expertise through publications in leading peer-reviewed scientific journals and experience in developing machine learning software, are required.
- Internationally leading research record in quantum Monte Carlo
- Familiarity with methods of computational quantum chemistry
- Experience in the development and application of machine-learning pipelines
- Strong knowledge of software frameworks for implementing GPU-accelerated computations, in particular JAX and PyTorch
- Knowledge of HPC environments and experience in efficiently scaling scientific software on computing clusters
- Experience in managing and further developing open-source software projects, as well as in creating and maintaining scientific and technical software documentation
- Teaching experience at universities or comparable academic institutions
- Presentation of own research results at international scientific conferences
- Gender and Diversity Competence
Benefits and Other Advantages
- Salary in line with the collective agreement for the civil service at the state level (TV-L FU), plus additional one-off annual payment
- Flexible working hours and mobile working by arrangement, where possible
- Thirty days of vacation (based on a five-day working week)
- Office closed on December 24 and December 31
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Fachbereich Mathematik und Informatik - Institut für Mathematik Arbeitgeber: Freie Universität Berlin
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