University of Oslo
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PhD in Data Attribution for Large Language Models (ML/NLP/AI) 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 and TRUST are recruiting PhD fellows in machine learning, NLP, and AI at the University of Oslo and UiT. One of the openings is Project #3: Data attribution for large language models, based at the University of Oslo, Faculty of Mathematics and Natural Sciences, Department of Mathematics.
This project focuses on a major explainability challenge in modern AI: tracing which parts of the training data influence an LLM’s answers. The research aims to develop scalable data attribution methods that go beyond simple scores and can disentangle factual versus linguistic influences. Possible directions include Shapley-value approximations, influence functions, surrogate attribution models, and multi-faceted attribution frameworks. The methods will be tested in settings such as fine-tuning, learning from examples, and open-weight language models.
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, Python, and deep learning frameworks is an advantage.
Funding: the position is fully funded and lasts three years. Fellows join a collaborative research environment with access to Integreat and TRUST activities, networks, seminars, workshops, mentoring, and interdisciplinary collaboration.
Application window: the deadline is 9 August 2026 at 23:59 CEST. Applicants submit one application and rank up to three projects. An online information meeting is held on 22 July 2026 at 19:00 CEST.
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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