In order to fill a fixed-term position in full-time (39.83 hours/week = 100%;) May 1st , 2026, we are looking for 1
Researcher (m/f/d) – AI-Enhanced Streaming Data Systems
The Database Systems Chair at Ruhr-Universität Bochum (RUB) is establishing a new research group focusing on learned and AI-enhanced counterparts for streaming data systems, including multimodal streaming workloads. We are seeking motivated researchers (m/f/d) to explore learning-based methods that augment or replace classical components in modern stream processing engines, with a strong focus on practical systems research.
Scope: full-time
Duration: fixed-term, 36 months
Start: May 1st , 2026
Apply by: 2026-02-28
Your tasks:
- Your responsibilities include:
- Research on learned components for streaming data systems, such as
- learned cost, latency, and throughput models for continuous and multimodal queries,
- learning-based scheduling, parallelism, and resource allocation for streaming operators, and
- learned strategies for runtime adaptation under changing workloads.
- Exploring the use of machine learning and, where appropriate, large language models (LLMs) to support system optimization, configuration, or semantic processing in streaming pipelines.
- Integrating learned components into existing streaming architectures and evaluating them alongside classical mechanisms.
- Designing and implementing experimental prototypes and system extensions.
- Conducting experimental evaluations on realistic streaming and multimodal workloads.
- Publishing research results in leading international data management and systems venues such as SIGMOD, VLDB, EDBT, ICDE or AI conferences such as NeurIPS, AAAI, ICML, ICLR.
- Presenting research results through talks, demonstrations, and scientific publications.
- Opportunity to contribute to teaching activities of the Database Systems Chair.
Your profile:
We welcome applications from candidates with a systems background and an interest in learning-based approaches.
- An excellent university degree (Master’s or equivalent) in computer science or a closely related field.
- Basic knowledge or practical experience in database systems, stream processing, or distributed systems.
- Interest in learning-based techniques for system optimization and performance modeling; prior ML experience is helpful but not mandatory.
- Programming experience in Python or similar languages; experience with Linux-based development environments is beneficial.
- Experience with streaming systems, multimodal data, or large language models (LLMs) is a plus, but not a prerequisite.
- Publications in leading conferences in the field of Data Management (SIGMOD, VLDB, ICDE, EDBT (having a publication is a plus, but it's optional)
- Motivation to work on systems research and to learn new techniques as part of a collaborative research group.
- Very good command of English; knowledge of German is not required.
https://jobs.ruhr-uni-bochum.de/jobposting/5cc4c477f9a03373df6c7e4ddfb5093837b426770?ref=AfA