For the Applied High-performance Computing working group of the Distributed Algorithms and Supercomputing department, we are offering a position, starting as soon as possible, on a full-time basis (39,4 hours per week), limited until September 30, 2027. If the applicant meets the relevant wage requirements and personal qualifications, the salary will be based on remuneration group 13 TV-L of the pay scale for the German public sector.
Researcher (f/m/d)
Zuse-Institut Berlin
Full-time
Temporary
61,193.82 - 86,189.54 € pro Jahr
Position Details
Background & Context
We are looking for a motivated early-career researcher who has completed a Master's degree in computational science, physics, or chemistry and wants to work at the interface of electronic structure theory, machine learning, and high-performance computing.
The position is embedded in an interdisciplinary team of physicists, chemists, and computer scientists working on chemical structure prediction. The work has two parts: an electronic-structure study and a supporting role in the group's dataset and machine learning activities. Both are carried out on NHR@ZIB's HPC systems.
Your Tasks
The successful candidate will conduct research at the intersection of mathematical optimization, first-order methods, and heuristic algorithm design. The work combines theoretical foundations, algorithmic development, and software implementation in an oracle-based solver framework.
- Completion of a DFT/TDDFT study of molecular electronic and excited-state properties using Gaussian 16 and related quantum chemistry codes, and prepare the results for publication in a peer-reviewed journal
- Performance of high-throughput reference calculations on HPC resources, including the setup and automation of workflows, submission and monitoring of jobs, and quality control of the resulting data
- Management and preprocessing of large molecular datasets for model training
- Support for the training, validation, and testing of neural network models, including the performance of experiments, benchmarks, and ablation studies in PyTorch as well as the analysis and documentation of results
- Contribution to the group’s open-source codebase, including software testing and documentation
- Collaboration with colleagues from physics, chemistry, and computer science on problems in chemical structure prediction
Your Profile
- A master’s degree in computational science, physics, chemistry, or a related field, with a thesis focusing on computational or quantum chemistry
- Practical experience with DFT and TDDFT calculations using Gaussian 16 or comparable quantum chemistry software
- Proficiency in Python and relevant scientific computing libraries, such as NumPy, SciPy, and pandas
- Initial experience with machine learning in a chemistry or physics context, for example in training and evaluating neural networks using PyTorch
- Experience working in Linux and HPC environments, including shell scripting and job submission using a batch scheduler such as SLURM
- Very good written and spoken English, combined with a collaborative working style
Ideally, you also have:
- Experience with GPU-accelerated model training
- Familiarity with Git-based collaborative software development and code review
- Experience in constructing or curating molecular datasets
- German language skills
What you can expect
We offer a friendly work environment with flexible work and meeting times, excellent equipment and a challenging professional environment
- comprehensive training in a competent and cooperative team,
- professional training opportunities and support in professional development,
- an additional pension scheme (VBL),
- 30 days annual leave, flexible working hours (flexitime),
- a salary based on TV-L (collective agreement for the public service of the federal states) in accordance with qualifications and professional experience with annual bonus payment,
- capital allowance of up to € 150 per month, or alternatively a BVG job ticket plus the remaining balance,
- the use of canteens and sports programs of the Freie Universität Berlin (FUB) at reduced rates.
The Zuse Institute Berlin is committed to diversity, equal opportunities, and a respectful and inclusive working environment. In order to increase the proportion of women in areas where they are underrepresented, we expressly encourage women to apply. Irrespective of this, we welcome applications from all qualified candidates regardless of age, disability, ethnic or social background, religion or belief, sexual orientation, or gender identity.
Please apply via our online application form by September 16, 2026, submitting your complete application including curriculum vitae in tabular form and the standard supporting documents.
Our private policy statement regarding application data is available at www.zib.de/impressum.
For further job offers please visit our website at www.zib.de/jobadvertisement.
Contact
For further information about the position, please refer to our website www.zib.de or contact Dr. Florian Schintke (schintke@zib.de).
Über uns
Das Zuse-Institut Berlin ist ein interdisziplinäres Forschungsinstitut für angewandte Mathematik und datenintensives High-Performance-Computing. Die Forschung konzentriert sich auf die Modellierung, Simulation und Optimierung in Zusammenarbeit mit wissenschaftlichen Kooperationspartnern aus Wissenschaft und Wirtschaft.