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About the Role
The Algorithms for Innovative Architectures workgroup is seeking a full-time researcher to contribute to the development of mathematical methods and digital decision-support systems for data-intensive modeling, simulation, and optimization. This role focuses on developing algorithmic and software solutions for efficient data-driven workflows on high-performance computing architectures.
Responsibilities
- Porting and adapting scientific simulation codes and AI workloads to modern computing architectures, including accelerators, GPUs, and emerging CPU architectures.
- Evaluating the performance and energy efficiency of ported codes and platforms using benchmarks.
- Analyzing network topologies and utilizing programmable NIC capabilities for AI workloads on HPC interconnects.
- Optimizing the next-generation Omni-Path interconnect for the DAOS HPC object store and evaluating its key-value store performance.
- Preparing and presenting research findings for publication in international conferences and scientific journals.
- Contributing to the group’s open-source codebases, including testing and documentation.
Requirements
- 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.
- 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.
- Ability and willingness to prepare and publish scientific work for an international audience.
- Very good spoken and written English.
- A collaborative working style.
- Experience with GPU-accelerated programming.
- Familiarity with Git-based collaborative development and code review.
Skills
- C
- C++
- Fortran
- Python
- Linux
- GPU-accelerated programming
- Git
Location
- Berlin
Work Type
- Full-time
- Limited until March 31, 2029
Experience Level
- Based on qualifications and professional experience
Education Level
- Master’s or Diplom degree in computer science, mathematics, or a related subject
Salary/Compensations
- Remuneration group 13 TV-L of the pay scale for the German public sector
- Salary based on TV-L in accordance with qualifications and professional experience with annual bonus payment
Benefits
- Friendly work environment
- Flexible work and meeting times
- Excellent equipment
- Challenging professional environment
- Comprehensive training in a competent and cooperative team
- Professional training opportunities and support in professional development
- Additional pension scheme (VBL)
- 30 days annual leave
- Flexible working hours (flexitime)
- Capital allowance of up to €150 per month
- Alternatively, a BVG job ticket plus the remaining balance
- Use of canteens and sports programs of the Freie Universität Berlin (FUB) at reduced rates
About the Company
- 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.
- ZIB develops computational methods to address challenges of societal relevance and provides state-of-the-art infrastructure for high-performance computing, artificial intelligence, and data management.
- 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.
Equal Opportunity
- The Zuse Institute Berlin is committed to diversity, equal opportunities, and a respectful and inclusive working environment.
- We expressly encourage women to apply to increase the proportion of women in areas where they are underrepresented.
- We welcome applications from all qualified candidates regardless of age, disability, ethnic or social background, religion or belief, sexual orientation, or gender identity.