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Position Details
For the Algorithms for Innovative Architectures workgroup of the Distributed Algorithms and Supercomputing department, we are offering this position, starting as soon as possible, on a full-time basis (39,4 hours per week), limited until March 31, 2029. 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.
Background & Context
The position is embedded in the HPCLab of Research Campus MODAL, a public–private research partnership involving the Zuse Institute Berlin (ZIB) and Freie Universität Berlin. MODAL develops mathematical methods and digital decision-support systems for data-intensive modelling, simulation and optimisation in areas such as energy, health and mobility. Within this interdisciplinary setting, the HPCLab develops algorithmic and software solutions to run data-driven optimisation and simulation workflows efficiently on emerging high-performance computing architectures, including heterogeneous processors, high-speed networks and modern storage systems.
Your Tasks
Porting and adaptation of representative scientific simulation codes and AI workloads to modern computing architectures, including NextSilicon’s Maverick-2 dataflow accelerator, GPUs and emerging CPU architectures such as RISC-V, with FPGA implementations where appropriate
Evaluation of the performance and energy efficiency of the resulting ports and platforms using application-specific benchmarks
Analysis of network topologies and use of programmable NIC capabilities for representative AI workloads on modern HPC interconnects, including InfiniBand and Cornelis Networks’ Omni-Path, as well as emerging fabrics for HPC and AI
Optimization of the next-generation Omni-Path interconnect to support the DAOS HPC object store for MODAL-relevant application patterns, and evaluation of the performance of its native key-value store
Preparation and presentation of research findings for publication at peer-reviewed international conferences and in scientific journals
Contributions to the group’s open-source codebases, including testing and documentation
Your Profile
A university degree (Master’s or Diplom) in computer science, mathematics, or a related subject
Knowledge of computer architectures, accelerators, networks, and data management systems
Programming experience, preferably in C, C++, Fortran, and Python, and routine use of Linux, including the command line
A strong interest in new research questions, their solution, and the practical implementation of research results
A high degree of independence and commitment, as well as the ability and willingness to prepare and publish scientific work for an international audience
Very good spoken and written English, and a collaborative working style
Ideally, you also have:
Experience with GPU-accelerated programming
Familiarity with Git-based collaborative development and code review
What you can expect
We offer a friendly work environment with flexible work and meeting times, excellent equipment and a challenging professional environment as well as:
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
Please apply via our online application form by November 22, 2026.
Contact
For further information about the position, please refer to our website www.zib.de or contact Dr. Florian Schintke ().
About us
The Zuse Institute Berlin (ZIB) is an interdisciplinary research institute of the State of Berlin, combining artificial intelligence and scientific computing with applied mathematics and high-performance computing. Together with partners from academia, technology and industry, we develop computational methods to address challenges of societal relevance and provide state-of-the-art infrastructure for high-performance computing, artificial intelligence and data management.
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