Facts
- Number of employees
- ca. 7000
- Category
- Research assistant
- Location
- Germany, Berlin, Charlottenburg
- Area of responsibility
- Academia and research, Research (academic), Teaching (university)
- Start date (earliest)
- Earliest possible
- Duration
- for 4 years
- Full/Part-time
- full-time; part-time employment may be possible
- Remuneration
- Salary grade 14 TV-L Berliner Hochschulen
- Homepage
- https://www.tu.berlin/en/rsim
Requirements
- Qualification
- Master, Diplom or equivalent and PhD
- Field of study
- Computer science, Künstlicher Intelligenz, Maschinelles Lernen
Contact
- Reference number
- IV-171/26
- Contact person
- Prof. Dr. Begüm Demir
Apply
- Application deadline
- 15.05.2026
- Reference number
- IV-171/26
- By email
- jobs@rsim.tu-berlin.de
Research Associate (PostDoc) - for qualification
part-time employment may be possible
About us
Join the 'Berlin Institute for the Foundations of Learning and Data' (BIFOLD; www.bifold.berlin) as a doctoral researcher, where you will contribute to cutting-edge research in Data Management, Machine Learning, and their intersection. BIFOLD conducts scalable agile fundamental research in the field of AI in the German AI metropolis of Berlin. The institute is part of the network of six national competence centers for artificial intelligence research in Germany. Their joint task is to further establish Germany’s leading position as top-tier location for research on AI technologies.
Your responsibility
The Big Data Analytics for Earth Observation group (https://rsim.berlin) 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.
How to apply
Please send your application, quoting the job reference number and including the usual documents (in particular, letter of motivation, latest CV, copies of your Bachelor's and Master's certificates, official copies of your academic transcripts, list of publications, and names and contact details of at least 2 referees whose letters should be available by the deadline of this call), preferably in English, only by e-mail as one file in PDF format to Prof. Dr. Begüm Demir, at jobs@rsim.tu-berlin.de.
By submitting your application via email you consent to having your data electronically processed and saved. Please note that we do not provide a guaranty for the protection of your personal data when submitted as unprotected file. Please find our data protection notice acc. DSGVO (General Data Protection Regulation) at the TU staff department homepage: https://www.abt2-t.tu-berlin.de/menue/themen_a_z/datenschutzerklaerung/.
To ensure equal opportunities between women and men, applications by women with the required qualifications are explicitly desired. Qualified individuals with disabilities will be favored. The TU Berlin values the diversity of its members and is committed to the goals of equal opportunities. Applications from people of all nationalities and with a migration background are very welcome.