Publisher
source

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 available

Deadline

Aug 9, 2026

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Country

Norway

University

University of Oslo

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Keywords

Computer Science
Information Technology
Mathematics
Artificial Intelligence
Natural Language Processing
Explainable Ai
Statistics
Linguistics
Large Language Models
Machine learning

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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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