Research Associate
(m/f/d) /
Wissenschaftliche*r Mitarbeiter*in
Institute Institute of Machine Learning in Virtual Materials Design
Remuneration EG 13 TV-L
ID: 31725WMEXK5
Start of employment February 1st 2026
Application deadline November 26th 2025
Scope full time, limited until January 31st 2028
Join a research group at the intersection of artificial intelligence and the engineering sciences. We are developing large language model (LLM) frameworks tailored to engineering knowledge, reasoning, and scientific discovery. The project aims to push beyond generic AI systems toward domain-adapted models and agentic frameworks capable of interpreting experimental data and simulations across diverse engineering disciplines. This is a position in which your creative spark is not only welcome, but essential!
You will work on creating the next generation of LLMs for engineering, exploring how these models can understand physical systems, assist in modeling and design tasks, and accelerate the development of intelligent research assistants for engineers.
YOUR TASKS
- Design and develop LLM-based frameworks for analyzing, summarizing, and reasoning over complex engineering data
- Build AI pipelines that integrate symbolic reasoning, simulation data, and multimodal information (e.g., text, images, CAD)
- Investigate methods for domain adaptation and alignment of LLMs to scientific and engineering contexts (e.g., fine-tuning, retrieval-augmented generation, reinforcement learning from scientific feedback)
- Collaborate with researchers across engineering disciplines to embed AI capabilities into modeling, design, and experimental workflows
- Publish your work in leading AI and engineering journals and contribute to open, reproducible research software, teach and support courses
YOUR PROFILE
Requirements
- Completed scientific university studies, in particular in the subject Machine Learning, Computer Science, Computational Engineering or related fields
Required knowledge and personal skills
- Very good English required (at least B2/C1 level according to CEFR) – German is not mandatory. Language support available.
- Solid background in large language models, natural language processing, or machine learning
- Proficiency in Python and experience with data handling or AI frameworks (e.g., PyTorch, Hugging Face, LangChain)
- Curiosity and teamwork skills for working in interdisciplinary teams
OUR OFFER
- further scientific training is possible, the results can be used for a dissertation
- flexible and family-friendly working conditions
- possibility of mobile working
- 30 day vacation per year
- good public transport connections
- comprehensive training and further education programs
At the heart of TU Hamburg’s research, teaching and transfer of technology is the guiding principle of developing technology for people. The TU Hamburg sees itself in this context as a family-friendly and sustainable university with high performance and quality standards that strives for excellence in all its research fields. Interdisciplinarity, innovation, regionality and internationality are binding principles in our actions.
With currently around 8.000 students, 110 professors and 1.650 employees, the TU Hamburg is characterised by short decision-making processes and close cooperation between the board, the institutes, the deans of studies, the research areas and the administration. We identify ourselves with a modern leadership culture and cultivate appreciative interaction.
For further information please contact Prof. Dr. Roland Aydin, Tel.-Nr. +49 40 30601 8111, Email: roland.aydin@tuhh.de
We value diversity, therefore all applications are welcome, regardless of gender, gender identity, ethnic origin, nationality, age, religion and belief, disability, sexual orientation and identity or social background.
The TUHH stands for equal opportunities as well as appreciative and respectful cooperation.
The TUHH stands for equal opportunities as well as appreciative and respectful cooperation.
Please send your complete application documents (cover letter, curriculum vitae in table form, proof of completed training and/or university degree, job references or certificates of employment) via the online application system.
Notice for severely disabled persons and people with equal status.
Notice for graduates of foreign educational qualifications:
Please submit proof of all obtained university degrees and, if available, the recognition of your educational qualifications in Germany (e.g. anabin excerpts and/or acknowledgement of previous employers).
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Please submit proof of all obtained university degrees and, if available, the recognition of your educational qualifications in Germany (e.g. anabin excerpts and/or acknowledgement of previous employers).
Seite drucken
