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Christian Hardmeier
4 months ago
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PhD Positions in Uncertainty Quantification and Communication for Large Language Models IT University of Copenhagen in Denmark
Degree Level
PhD
Field of study
Computer Science
Funding
Fully funded PhD position(s) with employment and enrollment at the IT University of Copenhagen for 3 or 4 years depending on degree level. Salary and terms follow the Danish AC agreement and university academic staff job structure. The project includes an extended research stay at the University of Edinburgh.
Deadline
Expired
Country
Denmark
University
University of Copenhagen
Suggested positions
Keywords
About this position
Two PhD positions are available in a project on Uncertainty Quantification and Communication for Large Language Models. The positions are based at the IT University of Copenhagen in Denmark and are jointly led by Christian Hardmeier and Jes Frellsen, with an extended research stay at the University of Edinburgh involving Hannah Rohde and Ivan Titov.
The first position focuses on natural language processing and aims to develop methods that help LLMs express uncertainty in ways humans can understand, while aligning communicated confidence with the model’s internal state. The second position focuses on machine learning and aims to develop efficient methods for quantifying uncertainty in large language models.
The project sits at the intersection of computer science, information technology, statistics, mathematics, and linguistics, with a strong emphasis on data science, experimental linguistics, semantics/pragmatics, and user studies with human participants. Applicants should have a relevant degree in computational linguistics, NLP, data science, AI, computer science, experimental linguistics, or a related field, plus strong Python skills. Experience with natural language data, PyTorch, LLM training/fine-tuning/evaluation, psycholinguistic studies, and academic publishing is desirable.
These are fully funded PhD positions with employment and enrollment at ITU for 3 or 4 years depending on the applicant’s degree level. Salary and employment terms follow the Danish university agreement. The application must be submitted in English and include a cover letter, CV, degree documentation, statement of purpose, and English proficiency documentation, with publications or thesis recommended if available.
Deadline: 24 June 2026 for the ITU position. The post also mentions a second related PhD position at DTU with deadline 7 August 2026.
Funding details
Fully funded PhD position(s) with employment and enrollment at the IT University of Copenhagen for 3 or 4 years depending on degree level. Salary and terms follow the Danish AC agreement and university academic staff job structure. The project includes an extended research stay at the University of Edinburgh.
What's required
Applicants must have a master’s degree or equivalent for the 3-year programme, or a bachelor’s degree plus one year of master’s-level study for the 4-year programme, in computational linguistics, natural language processing, data science, artificial intelligence, computer science, experimental linguistics, or a related field. Strong Python programming skills are required. Desirable qualifications include experience with natural language data, PyTorch or similar machine learning frameworks, training/fine-tuning/evaluating large language models, knowledge of semantics or pragmatics, psycholinguistic studies with human participants, and academic publishing experience. English proficiency documentation is required, and applications must include a motivated application, CV, degree documentation, statement of purpose, and relevant publications or thesis if available.
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Professors
Associate Professor
Denmark
Research Interests
Psycholinguistics
Computational Linguistics
Linguistics
Large Language Models
Machine Learning
Professor
Denmark
Research Interests
Psycholinguistics
Computational Linguistics
Large Language Models
Natural Language Processing
Information Technology
Professor
Denmark
Research Interests
Computational Linguistics
Psycholinguistics
Large Language Models
Computer Science
Machine Learning
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.