The DLR Institute of Data Science in Jena focuses on finding solutions to the new challenges of the digitalization era. Research concentrates on the areas of data management, data analysis and data acquisition. Three departments have been set up in line with the thematic focus of the institute.

In the Data Analysis and Intelligence department, methods are developed and applied that enable the analysis of complex and large data sets. Here, methods of machine learning, causal inference and domain-specific process knowledge are used. To increase the technology transfer potential, human factors such as acceptance are considered during application development.

What do we offer

In the "Machine Learning" working group, we research and develop innovative data-driven methods for data analysis and, in cooperation with other DLR institutes, find solutions for practical applications using machine learning methods.

As part of our working group, we offer you the opportunity to write your thesis or work as a student in the field of machine learning, specifically on the topic of model compression of foundational models like Large Language Models (LLMs) in combination with privacy preserving approaches. As part of an international team, your task will be to help design, implement and evaluate new methods.

Your tasks

• Implementing and testing LLM compression methods such as pruning, quantization, and low-rank adaptation.
• Running experiments with open-source LLMs such as LLaMA, Phi, Mistral, Gemma, or Qwen models.
• Evaluating compressed models on reasoning, question-answering, and language understanding benchmarks.
• Supporting experiments on privacy-preserving AI methods, such as federated learning, differential privacy, secure inference, or homomorphic encryption.
• Reading and summarizing recent research papers related to efficient and trustworthy LLMs.
• Contributing to internal tools for LLM compression and evaluation.
• Test and documentation of the work, incl. preparing scripts, experiment logs, plots, and result tables.

As part of your student work, you will be responsible for up to 20 hours of work per week. The exact topic of a thesis will be defined together with you according to your specific qualifications and expectations.

What you bring with you

• Ongoing studies in computer science, mathematics, physics, data science, or related subjects
• Basic knowledge of mathematics (analysis, linear algebra, stochastics, logic)

• Good programming skills in Python.
• Familiarity with PyTorch, Hugging Face Transformers, and similar libraries.
• Interest in large language models, trustworthy, and efficient AI systems.
• Good English knowledge

Evidence of completed projects, e.g. university coursework, internship, etc.  

 We look forward to getting to know you!

If you have any questions about this position (Vacancy-ID 5387) please contact:

Prof. Christian Thiel 
Tel.: +49 3641 30960 128