Siegfried Handschuh
1 week ago
PhD Position in Foundation Models and Efficient LLM Training at the University of St. Gallen University of St. Gallen in Switzerland
Degree Level
PhD
Field of study
Computer Science
Funding
Fully funded PhD position with access to modern compute infrastructure, support for publishing at top-tier conferences, and full supervision and mentoring throughout the PhD.
Country
Switzerland
University
University of St. Gallen

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About this position
PhD position at the Institute of Computer Science (ICS-HSG), University of St. Gallen, in the DS-NLP Lab with Prof. Dr. Siegfried Handschuh. The project focuses on foundation models, efficient LLM training, and natural language processing, with research topics including training dynamics of large language models, scaling behavior, optimization, generalization, token weighting strategies, dataset construction, and large-scale data processing.
The role combines doctoral research with teaching duties (about 2 SWS per semester), including tutorials, exercises, and supervision of Bachelor’s and Master’s theses and projects. The position also includes organizational and research-related support for the chair.
Applicants should have a master’s degree in computer science, machine learning, computational linguistics, or a related field. Strong Python skills are required. Helpful experience includes NLP/ML research, publications, PyTorch or TensorFlow/Keras, and interest in efficient training methods such as LoRA, quantization, sparsity, and distillation. A background or strong interest in linguistics or computational linguistics is especially welcome.
The position is fully funded and offers access to modern compute infrastructure, a collaborative international environment, and support for publishing at top-tier conferences. The post states a limited appointment starting 01.11.2026.
Apply online using job ID 2800 via the provided application portal.
Funding details
Fully funded PhD position with access to modern compute infrastructure, support for publishing at top-tier conferences, and full supervision and mentoring throughout the PhD.
What's required
Applicants must hold a master's degree in computer science, machine learning, computational linguistics, or a related field. Strong programming skills in Python are required. Desirable qualifications include prior research experience or publications in NLP, ML, or related areas, experience with PyTorch or TensorFlow/Keras, and interest or experience in training large language models, efficient training techniques such as LoRA, quantization, sparsity, and distillation, scaling laws, training dynamics, evaluation of generative models, dataset construction, large-scale data processing, and linguistics or computational linguistics, especially tokenization and token weighting strategies. Candidates should be able to work independently, structure their research, manage time effectively, and contribute to teaching and collaborative research.
How to apply
Apply online using job ID 2800 via the provided application portal. Use the job-specific application link and submit the required materials through the HSG online application system.
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