Lehrstuhl für Data Science and Natural Language Processing

Zitat ergänzen

Lehrstuhl für Data Science and Natural Language Processing

Zitat ergänzen

• You will work on your doctoral thesis in the area of foundation model training and
  efficient learning methods
• You design and conduct research on training dynamics of large language models,
  including scaling behavior, optimization, and generalization
• You incorporate linguistic insights into the development and analysis of language
  models, with a particular focus on token weighting strategies and their effects on
  training dynamics
• You engage in teaching activities (approx. 2 SWS per semester), including tutorials,
  exercises, and supervision of Bachelor’s and Master’s theses and projects
• You support the chair in organizational and research-related tasks

• You hold a master’s degree in computer science, machine learning, computational
  linguistics, or a related field
  o Desirable: prior research experience or publications in NLP, ML, or related
  areas
• You have strong programming skills in Python
• Desirable: experience with PyTorch, or TensorFlow/Keras
• You have experience or strong interest in:
• Training large language models (transformers)
• Efficient training techniques (e.g., LoRA, quantization, sparsity, distillation)
• Scaling laws, training dynamics, or evaluation of generative models
• Dataset construction and large-scale data processing
• Desirable:
• Background or interest in linguistics or computational linguistics, particularly
  in relation to tokenization and token weighting strategies
• You are able to work independently, structure your research, and manage your time
  effectively
• You are motivated to contribute to teaching and collaborative research

We offer

• fully funded PhD position in a dynamic and fast-growing research area
• Access to modern compute infrastructure
• Support for publishing at top-tier conferences
• A collaborative and international research environment
• Full supervision and mentoring throughout your PhD journey