University of Oslo
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PhD in Data Attribution for Large Language Models and Machine Learning in Norway University of Oslo in Norway
Degree Level
PhD
Field of study
Computer Science
Funding
Full funding availableDeadline
Aug 9, 2026
Country
Norway
University
University of Oslo

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About this position
Integreat is recruiting 8 fully funded PhD fellows in Norway in knowledge-driven machine learning, with positions at the University of Oslo and UiT The Arctic University of Norway. One highlighted project is Data attribution for large language models, focused on understanding which parts of training data influence LLM outputs and how to disentangle factual versus linguistic effects.
This PhD project sits at the intersection of computer science, machine learning, natural language processing, statistics, and mathematics. The research aims to develop scalable and informative attribution methods beyond simple scalar scores, with possible directions including Shapley-value approximations, influence functions, surrogate attribution models, and multi-faceted attribution frameworks. The methods will be evaluated in LLM settings such as fine-tuning, learning from examples, and open-weight language models.
The position is affiliated with the Faculty of Mathematics and Natural Sciences in Oslo and is jointly supervised by Ingrid K. Glad and Martin Jullum. The broader Integreat call includes interdisciplinary projects spanning machine learning, statistics, logic, language technology, and ethics, and fellows join a collaborative research community with access to seminars, workshops, mentoring, and international collaboration opportunities.
Eligibility highlights: applicants should hold a Master’s degree or equivalent in computer science (AI/ML/NLP), mathematics, statistics, or a related field, and have strong programming skills. Experience with NLP, LLMs, explainable AI, data attribution, Shapley values, and Python/deep learning frameworks is an advantage.
Funding: the position is fully funded and lasts three years. Deadline: 9 August 2026, 23:59 CEST. Applicants submit a single application and rank up to three projects in order of preference.
Funding details
Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.
How to apply
Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.
More information can be found here
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