Research Associate

vor 3 Wochen

Oldenburg, Deutschland Carl von Ossietzky Universität Oldenburg Vollzeit

**Research Associate** (M/F/d) (Pay group E13 TV-L, 50%)
with focus on** Online & Offline Deep Reinforcement Learning in Critical Infrastructures**

until 31st of July 2025, with the possibility of extension.

ARL agents work on an advanced multi-agent auto-curriculum. Your research objective is to enable the agent to learn from domain knowledge, which is to integrate offline learning into the agent’s architecture. Moreover, your approach will help to counter the catastrophic forgetting problem that arises when the agent’s environment changes. Thus, your research will create a dynamic, advanced learning loop for reinforcement learning agents.

**Your Profile**:

- Successfully completed university degree (Master or Diploma (university)) degree in computer sciences
- profound knowledge in formalization techniques
- profound knowledge in domain knowledge formalization, such as (Mis-) Use Case modeling
- programming experience with at least Python or C++, software engineering knowledge is a bonus
- experience with online or offline learning algorithms is an additional bonus
- fluently spoken and written English.
- motivation and ability to publish and present scientific findings, represent the research group to international experts, and to collaborate with a diverse and international team of researchers; having experience in (co-) authoring articles is welcomed

**What We Offer**:

- An existing environment for research within a productive and prestigious junior research group that has immediate impact on CNI operation
- Freedom to shape your research according to the group’s goals
- International network of partner universities as well as industry partners
- Opportunity for a fast-paced PhD in a prestigious, BMBF-funded junior research group along with publications and presentations on international conferences

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