Research Associate (E14, RSiM, IV-171/26)
Your responsibility
The Big Data Analytics for Earth Observation at BIFOLD seeks to employ a postdoctoral researcher in the field of AI Agents for Earth observation (EO) that interact with the users about the environmental and climate issues. Over the past few years, foundation models have fundamentally transformed the landscape of Earth observation, enabling effective and efficient large-scale EO data understanding. Building upon these advances, AI Agents (which are designed to facilitate a seamless interaction with the vast data from the satellite data archives and powered by multimodal foundation models) are rapidly emerging as a central paradigm for decision-making in EO. The selected candidate will conduct research in generative, multimodal, and agentic AI for Earth observation. In detail, the topics include but not limited to design and development of: 1) multi-agent systems; 2) hallucination detection and mitigation strategies; 3) post-training approaches; 4) self-evolving and efficient systems; and 5) evaluation and benchmarking frameworks. Besides conducting research, the successful candidate will have teaching duties, which includes mentoring Bachelor’s, Master’s and PhD students in addition to the coordination of interdisciplinary research projects.
Your profile
- Successfully completed university degree (Master, Diplom or equivalent) and PhD degree in computer science, artificial intelligence, machine learning, or a related field.
- Strong background in one or more of the following areas: AI agents, large language models, vision-language models, multimodal learning, and generative AI. Successful applicants will be strong technically as well as have an inclination towards real-world problems.
- Scientific experience as demonstrated via relevant scientific publications and solid knowledge in theoretical and applied/practical computer science.
- Excellent programming skills (e.g., python) with experience using generative AI libraries.
- Strong communication skills is an advantageous.
- The ability to teach in German and/or in English is required; willingness to acquire the respective missing language skills.
- Experience in teaching and didactic competence is an advantageous.
- Experience in open-source development is an advantageous.
- Experience in project management is an advantageous.
Salary grade: TV-L 14, Berliner Hochschulen
Starting date: Earliest possible
Closing date: May 15, 2026
Full job posting: IV-171/26