Zuse Institute Berlin (ZIB) is a non-university research institute under public law of the state of Berlin. Since January 2021, the ZIB has been extending its scientific services by offering HPC consulting for scientists in Germany and international projects as part of the nationwide HPC initiative “Nationales Hochleistungsrechnen” (NHR). We operate compute and storage resources at the Tier-2 level that enable demanding computational and AI workflows to solve complex scientific questions. The current HPC system comprises more than 140,000 compute cores and 256 GPUs of different architectures, and over 20 PB global persistent online storage. Within the NHR@ZIB center, we are offering a position at the earliest possible date for a

High-Performance Computing Data Scientist (f/m/d)

on a full-time basis (39,4 hours per week), limited until December 31st, 2030. If the applicant meets the relevant wage requirements and personal qualifications, the salary will be based up to remuneration group 14 TV-L of the pay scale for the German public sector. Subsequently, there is the possibility of a permanent contract.

The applicant will help users across multiple scientific domains to implement AI and data-intensive workflows efficiently on NHR HPC systems. The position requires collaborative interaction with users who develop and apply software frameworks for machine learning, AI, and related parts in data-driven science projects as well as focusing on performance aspects on the current and next-generation technology platforms. The applicant is encouraged to conduct his/her own research program in a data science related field.

We are looking for a candidate with a strong background in method development and software frameworks for AI/data analytics who is highly motivated to work in the converging area of high-performance computing and AI.

Your tasks

• Guiding the nationwide NHR user community to implement efficiently data-intensive and machine learning, AI, and other data-driven workloads
• Developing best-practice solutions for efficient multi-tiered data management
• Evaluating, adapting and contributing to optimized versions of machine learning/AI software
• Working jointly with other HPC experts to migrate code to next-generation HPC architectures
• Installing machine learning/AI software frameworks and developing best-practice solutions and documentation
• Contributing to nationwide NHR training activities including the NHR Graduate School for users of AI/data analytics frameworks
• Conducting your own research in the respective field, including the acquisition of third-party funded projects
• Publishing scientific results at international conferences and in journals (travelling will be supported by the ZIB)

Your profile

• University degree (master/diploma) with proven expertise in a AI/data-science related field, preferably on the interfaces between machine learning and simulation or optimization, in life science or similar areas; doctoral degree / PhD would be favorable
• Longtime professional experience in this field of activity, such as
  • good technical background on state-of-the-art technologies for machine learning / AI (AI-specific hardware and software), and parallel computer architectures (processors, high-performance interconnects, memory hierarchies, and storage systems)
  • experience in using frameworks for data processing / machine learning / AI software frameworks on parallel computer systems
  • background in parallel programming (multi-threading, message passing) using C/C++ and Python; experience with accelerators (GPU, AI, FPGA) would be desired
• Good understanding of data management technologies including parallel file systems, memory and multi-tier storage hierarchies
• Strong focus on self-reliance, pro-activity, creativity and the ability to work in a team

We offer

We offer a friendly work environment with flexible work and meeting times, excellent equipment and a challenging professional environment

as well as

• an active onboarding process to provide new employees with the skills and knowledge that are important to their success in our institute and their careers,
• a varied, future-oriented and responsible field of activity,
• 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,
• a subsidized BVG public transport job ticket,
• the use of canteens and sports programs of the Freie Universität Berlin (FUB) at reduced rates.

Applicants with disabilities will be given preference if equally qualified. Female applicants are highly encouraged to apply, since women are under-represented in natural sciences and ZIB seeks to increase the proportion of women in this field.

Contact

Please send your complete application including a cover letter containing a statement of your research interests, your CV with a list of publications, academic transcripts and contact details of two references by January 10th, 2026 (date of receipt), quoting the Reference Number WA 30/25 as one PDF file to: [email protected].

For further information about the position, please refer to our website www.zib.de, contact Dr. Thomas Steinke ( [email protected]).

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.