PhD fellowship in Natural Language Processing
PhD Project in Cultural Reasoning with Language Models
The AI Section at the Department of Computer Science invites applicants for a PhD fellowship in computational modelling and evaluation of cultural interpretation with language models. The position is part of the research project “CuRe: Cultural Reasoning for Responsible Language Model Development” (DFF project 5334-00088B), funded by Independent Research Fund Denmark.
The expected start date is February 1st, 2027 or as soon as possible thereafter.
The project
Language models can produce fluent interpretations of texts while obscuring the cultural assumptions, uncertainty and alternative readings underlying their answers. CuRe investigates how language models understand and reason about culture, ambiguity and interpretation, and how these capabilities can be evaluated and improved to support responsible language model development. Literary texts provide a demanding testbed: their interpretation depends on historical and cultural knowledge, close attention to textual evidence and the ability to accommodate several plausible readings.
The PhD candidate will develop computational methods and evaluation resources for culturally grounded interpretation. Working closely with researchers in natural language processing and literary studies, the candidate is expected to:
- construct datasets and benchmarks linking literary passages, relevant cultural and historical context, textual evidence and expert or reader interpretations;
- analyse what cultural knowledge and interpretive strategies language models use, where their interpretations fail and how confidently they present uncertain conclusions;
- develop methods for grounding interpretations in evidence and for representing uncertainty, ambiguity and multiple plausible interpretations;
- evaluate the resulting methods through automatic experiments and studies with literary scholars and other readers; and
- publish the results in leading venues in natural language processing, artificial intelligence and computational humanities.
The exact research questions will be refined together with the successful candidate. Relevant methodological directions include language model evaluation and probing, retrieval and retrieval-augmented generation, explicit representations of interpretive evidence and uncertainty, data annotation, human-centred evaluation and multilingual or cross-cultural analysis. The empirical work will primarily use modern Scandinavian literary texts, while aiming to develop methods and findings that generalise beyond literature. The project includes a planned research stay at McGill University.
Who are we looking for?
We are looking for candidates with a strong computational background and an interest in how language, culture and interpretation can be studied rigorously. Applicants may have a background in natural language processing, computational linguistics, computer science, machine learning, artificial intelligence, data science, digital humanities or a closely related field. Formal training in literary studies is not required, but the successful candidate must be motivated to work across disciplinary boundaries and to engage seriously with humanities research questions.
Our group and research- and what do we offer?
The PhD fellow will join the CoAStaL research group and the AI Section at the Department of Computer Science. The research environment brings together faculty, postdoctoral researchers and PhD students working on multilingual and cross-cultural NLP, multimodality, language model training and evaluation, responsible AI and computational humanities. The section collaborates broadly with leading research groups in Denmark and abroad.
CuRe is an interdisciplinary collaboration with the Department of Nordic Studies and Linguistics at the University of Copenhagen. The project builds on established joint work in computational literary studies and provides access to large literary corpora, domain expertise and relevant annotation resources. The PhD fellow will therefore be part of both a technically strong NLP environment and a close collaboration with literary scholars.
The group is part of the Department of Computer Science, Faculty of Science, University of Copenhagen. We are located in Copenhagen. We offer creative and stimulating working conditions in a dynamic and international research environment. Our research facilities include modern GPU computing resources, shared data and annotation infrastructure and access to relevant text corpora.
Principal supervisor: Associate Professor Desmond Elliott, Department of Computer Science, de@di.ku.dk.
Co-supervisor: Tenure-Track Assistant Professor Daniel Hershcovich, Department of Computer Science, dh@di.ku.dk.
Co-supervisor: Associate Professor Jens Bjerring-Hansen, Department of Nordic Studies and Linguistics, jbh@hum.ku.dk.
The PhD programme
The position is offered as a three-year full-time study within the framework of the regular PhD programme (5+3 scheme).
Qualifications needed
To be eligible for the regular PhD programme, you must have completed a degree programme, equivalent to a Danish master’s degree (180 ECTS/3 FTE BSc + 120 ECTS/2 FTE MSc) related to the subject area of the project, e.g. [relevant educations]. For information of eligibility of completed programmes, see General assessments for specific countries and Assessment database.
Terms of employment
The position is covered by the Memorandum on Job Structure for Academic Staff.
Salary, pension and other conditions of employment are set in accordance with the Agreement between the Ministry of Taxation and AC (Danish Confederation of Professional Associations) or other relevant organisation. Currently, the monthly salary starts at 31,800 DKK/approx. 4,200 EUR (August 2026-level). Depending on qualifications, a supplement may be negotiated. The employer will pay an additional 18,07 % to your pension fund.
Foreign and Danish applicants may be eligible for tax reductions, if they hold a PhD degree and have not lived in Denmark the last 10 years.
Responsibilities and tasks
- Carry through an independent research project under supervision
- Complete PhD courses corresponding to approx. 30 ECTS / ½ FTE
- Participate in active research environments, including a stay at another research institution, preferably abroad
- Teaching and knowledge dissemination activities
- Write scientific papers aimed at high-impact journals
- Write and defend a PhD thesis on the basis of your project
We are looking for the following qualifications:
- A master’s degree or equivalent qualification relevant to the PhD project.
- Strong programming skills, preferably in Python, and experience with machine learning or natural language processing tools.
- Knowledge of modern NLP and language models and an ability to design, implement and evaluate computational experiments.
- Experience with one or more of the following is an advantage: language model evaluation, retrieval or retrieval-augmented generation, data annotation, interpretability, multilingual NLP or computational humanities.
- Relevant research experience, publications, thesis work or professional activities.
- Ability to work independently, formulate research questions and collaborate across computer science and the humanities.
- A curious and critical mindset with a strong interest in culture, interpretation and responsible AI.
- Excellent written and spoken English. Knowledge of a Scandinavian language or experience with literary analysis is an advantage but not a requirement.
Application and Assessment Procedure
Your application including all attachments must be in English and submitted electronically by clicking APPLY NOW below.
Please include:
- Motivated letter of application (maximum one page) explaining your motivation for the project, your relevant qualifications and the research directions that particularly interest you.
- Curriculum vitae including information about your education, research or work experience, language skills and other skills relevant to the position.
- Original diplomas for bachelor’s and master’s degrees and transcripts of records in the original language, including an authorised English translation if issued in a language other than English or Danish. If the master’s degree has not yet been completed, a certified or signed recent transcript of records or a written statement from the institution or supervisor is accepted.
- Publication list, if applicable.
- Reference letters, if available.
Application deadline:
The deadline for applications is November 8th, 2026, 23:59 CET
We reserve the right not to consider material received after the deadline, and not to consider applications that do not live up to the abovementioned requirements.
The further process
After deadline, a number of applicants will be selected for academic assessment by an unbiased expert assessor. You are notified whether you will be passed for assessment.
The assessor will assess the qualifications and experience of the shortlisted applicants with respect to the above-mentioned research area, techniques, skills and other requirements. The assessor will conclude whether each applicant is qualified and, if so, for which of the two models. The assessed applicants will have the opportunity to comment on their assessment. You can read about the recruitment process at https://employment.ku.dk/faculty/recruitment-process/.
Interviews with selected candidates are expected to be held in week 49.
Questions
For specific information about the PhD fellowship, please contact the project supervisor Daniel Hershcovich at dh@di.ku.dk or +45 53 33 88 04.
[General information about PhD study at the Faculty of SCIENCE is available at the PhD School’s website: https://www.science.ku.dk/phd/].
The University of Copenhagen wishes to reflect the surrounding community and invites all regardless of personal background to apply for the position.
Part of the International Alliance of Research Universities (IARU), and among Europe’s top-ranking universities, the University of Copenhagen promotes research and teaching of the highest international standard. Rich in tradition and modern in outlook, the University gives students and staff the opportunity to cultivate their talent in an ambitious and informal environment. An effective organisation – with good working conditions and a collaborative work culture – creates the ideal framework for a successful academic career.