onsite
PhD Researcher in Machine Learning for Language Technologies - Friedrich-Alexander-Universitat Erlangen-Nurnberg
ML Engineer
Conduct cutting‑edge research on reasoning, interpretability, and neuro‑symbolic approaches to improve large language and vision‑language models for unseen tasks, domains, and languages, while publishing in top conferences and supporting teaching.
About the role
Key Responsibilities
- Design and implement novel machine‑learning, NLP, and reinforcement‑learning algorithms targeting long‑tail tasks, domains, and low‑resource languages.
- Investigate and advance reasoning, interpretability, and neuro‑symbolic techniques for large language and vision‑language models.
- Publish high‑impact research papers at top‑tier conferences and journals.
- Contribute to the laboratory’s teaching curriculum, deliver lectures, and supervise graduate and undergraduate students.
- Collaborate with interdisciplinary teams, present findings, and participate in research seminars.
Requirements
- Strong background in Machine Learning, Natural Language Processing, and Reinforcement Learning, demonstrated through prior research or projects.
- Experience with neuro‑symbolic methods, model interpretability, or related areas.
- Proficiency in Python and common ML frameworks (e.g., PyTorch, TensorFlow).
- Excellent scientific writing and communication skills; proven record of publications is a plus.
- Motivation to work independently while contributing to a collaborative research environment.
Skills
machine learningnatural language processingreinforcement learningpython