Research Assistant (E13, PhD candidate, RSiM, IV-223/25)

Working field:
At the Big Data Analytics for Earth Observation group (https://rsim.berlin) of BIFOLD, we are seeking to hire a Research Associate (Doctoral Researcher) interested in the design and development of foundation models for Earth observation. The selected candidate will focus on foundational research and current challenges in this field, including the development
of novel algorithms and methods, as well as prototype systems and software tools. Possible topics include multi-modal and cross-sensor representation learning; parameter-efficient finetuning of foundation models; merging of foundation models; and continual learning in the framework of foundation models.

The employment relationship is related to the regular teaching obligation (§ 5 para. 1 no.4 LVVO). Participation in the AI Competence Centre BIFOLD requires a special aptitude for working in research. The tasks at BIFOLD can justify according to § 1 S.2 LVVO a reduction in teaching duties.

Requirements:

Successfully completed academic university degree (Master, Diplom or the equivalent) in computer science (e.g., theoretical, methodological-practical, or technical computer science),
Knowledge of machine learning theories and methods (e.g., core methods, deep neural networks), practical experience in developing and applying ML algorithms, experience with linear algebra / neural network frameworks
(e.g., NumPy, PyTorch, TensorFlow, JAX),
Experience in remote sensing image analysis and some knowledge on large language models.
Good programming skills (e.g., Python, Java, C/C++),
The ability to teach in German and/or in English is required; willingness to acquire the respective missing language skills.

Salary grade: TV-L 13, Berliner Hochschulen
Starting date: Earliest possible (for 5 years)
Closing date: June 20, 2025
Full job posting: IV 223/25