About the position

Integreat – Norwegian Centre for Knowledge-driven Machine Learning is seeking a motivated PhD candidate in machine learning, knowledge representation, logic or statistics, to join our interdisciplinary research centre at the University of Oslo, Norway.

This is a unique opportunity to contribute to cutting-edge research at the intersection of machine learning, statistics, and logic—within a collaborative and supportive academic environment.

You will be part of a dynamic group of early career researchers, supervised by senior experts, collaborating across disciplines to tackle fundamental challenges through innovative methods, theory and critical analysis.

The fellowship period is 3 years.

Starting date as soon as possible and upon individual agreement.

An extension of the appointment by up to twelve months may be considered, which will be devoted to career enhancing compulsory work duties, e.g. teaching or supervision. This will be dependent on the qualifications of the applicant and the specific teaching need of the employment department.

No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo.

About Integreat

Integreat – Norwegian Centre for Knowledge-driven Machine Learning is a Centre of Excellence, funded by the Research Council of Norway (2023-33). Integreat has two branches, one in Oslo (University of Oslo, UiO) and one in Tromsø (UiT The Arctic University of Norway).

Machine learning is the mathematical and computational engine of Artificial Intelligence (AI), and therefore it is a fundamental force of technological progress in our increasingly digital, data- and algorithm-driven world. Integreat develops theories, methods, models, and algorithms that integrate general and domainspecific knowledge with data, laying the foundations of next generation machine learning. We do this by combining the mathematical and computational cultures, and the methodologies and theories, of statistics, logic, language technology, ethics and machine learning, in new and unique ways.

Focus of Integreat is to develop groundbreaking methods and theories, and therefore solving fundamental problems in science, technology, health and society. Integreat draws on the research strengths of researchers and students from the departments of Mathematics, Informatics, Philosophy, and the Oslo Centre for Biostatistics and Epidemiology at UiO, the Norwegian Computing Centre (NR) and the ML group at UiT, with members from the Departments of Physics and Technology, Mathematics and Statistics, and Computer Science.

Project description

This project links together knowledge graphs with uncertainty quantification in situations where domain knowledge can be exploited. Each of these research areas is vibrant and important on its own right, and this project aims to bring them together in a meaningful way. One of the most interesting frameworks for quantifying the uncertainty of predictions is conformal prediction (CP). Under appropriate conditions, it provides a confidence set (credibility set if prediction is Bayesian) for a multivariate estimate with statistical coverage guarantees. This PhD project aims to develop new CP methods for knowledge graphs (KGs), which are one of the most popular approaches for (semi-)structured data. There are many learning tasks on KGs, such as KG completion, link prediction, and node and graph classification. Graph Neural Networks (GNNs) are very successful for learning on KGs and solving the mentioned tasks, but also have great potential for incorporating symbolic knowledge due to strong connections between GNNs and logics. Such knowledge can be represented in common practical languages based on First Order Logic, as well as its fragments and extensions. We will develop methods for logic-aware CP on KGs using GNN for prediction and design new algorithms with theoretical guarantees. This PhD project will be at the interface between statistics, logic and machine learning.

Project supervisors: Egor V. Kostylev, Arnoldo Frigessi

Working language: English.

This position is at the University of Oslo, Integreat – Norwegian Centre for Knowledge-driven Machine Learning, and the Department of Informatics, with the place of work at Integreat.

The centre values inclusive excellence and is committed to fostering an environment where all voices are heard and respected.

We offer excellent opportunities for mentorship, international collaboration, and academic growth. If you are passionate about impactful research, eager to learn, or looking to grow in a team-oriented culture—we encourage you to apply and bring your perspective to our community.

What skills are important in this role?

The Faculty of Mathematics and Natural Sciences has a strategic ambition to be among Europe’s leading communities for research, education and innovation. Candidates for these fellowships will be selected in accordance with this, and expected to be in the upper segment of their class with respect to academic credentials.

Qualification requirements:

Master’s degree or equivalent in mathematics, statistics, computer science or similar.
Foreign completed degree (M.Sc.-level) corresponding to a minimum of four years in the Norwegian educational system.
The Master project should treat methodological aspects with mathematical tools.
Experience in scientific programming.

All candidates and projects will have to undergo a check versus national export, sanctions and security regulations. Candidates may be excluded based on these checks. Primary checkpoints are the Export Control regulation, the Sanctions regulation, and the national security regulation.

Personal skills:

We are looking for candidates who are curious, open-minded, and motivated to learn. You should enjoy working both independently and as part of a team, and be comfortable communicating your ideas clearly across disciplines. A collaborative spirit, a strong sense of responsibility, and a willingness to contribute to an inclusive and respectful research culture are essential.

Language requirement:

Good oral and written communication skills in English
English requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements:
https://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8

Grade requirements:
The norm is as follows:

the average grade point for courses included in the Bachelor’s degree must be C or better in the Norwegian educational system
the average grade point for courses included in the Master’s degree must be B or better in the Norwegian educational system
the Master’s thesis must have the grade B or better in the Norwegian educational system

Candidates without a master’s degree have until 01.09.2025 to complete the final exam.

The purpose of the fellowship is research training leading to the successful completion of a PhD degree. For more information see:
http://www.mn.uio.no/english/research/phd/

We can offer you

A unique research environment with multiple opportunities to develop research themes at the forefront of modern science
A friendly, inclusive, and collaborative international working environment that values diverse perspectives
Access to a strong network of top-level national and international collaborators
A reliable and generous pension agreement, along with strong public benefits
Comprehensive welfare schemes supporting both personal and professional well-being
Full access to public health services through membership in the National Insurance Scheme
A vibrant academic environment with an active and supportive research community
Career development programmes
Mentoring and support structures tailored to early-career researchers
Flexible working conditions, with understanding for different life situations and family responsibilities
Research mobility funds supporting short research stays and international collaboration
Family-friendly surroundings in Oslo and Tromsø, with rich opportunities for culture, nature, and outdoor activities
A clear institutional commitment to gender equality and diversity, with dedicated initiatives and networks for women in science
Membership in the Statens Pensjonskasse, which is one of Norway's best pension schemes with beneficial mortgages and good insurance schemes
Salary in position as PhD Research Fellow, position code 1017 in salary range NOK 536 200 – 575 400, depending on competence and experience. From the salary, 2 percent is deducted in statutory contributions to the State Pension Fund

Inclusive worklife and diversity at UiO

Inclusion and diversity are a strength. The University of Oslo has a personnel policy objective of achieving a balanced gender composition. Furthermore, we want employees with diverse professional expertise, life experience and perspectives.

If there are qualified applicants with disabilities, employment gaps or immigrant background, we will invite at least one applicant from each of these categories to an interview.

We hope that you will apply for the position.

More information about gender equality initiatives at UiO can be found here.

Application

Your application should include:

Cover letter - statement of motivation and research interests
CV (summarizing education, positions and academic work - scientific publications)
Copies of the original Bachelor and Master’s degree diploma and transcripts of records
Documentation of English proficiency if applicable
List of publications and academic work that the applicant wishes to be considered by the evaluation committee
The master thesis or at least some finished chapter of the master thesis
Names and contact details of 2-3 references (name, relation to candidate, e-mail and telephone number)

Application with attachments must be submitted via our recruitment system Jobbnorge, click "Apply for the position".

When applying for the position, we ask you to retrieve your education results from Vitnemålsportalen.no. If your education results are not available through Vitnemålsportalen, we ask you to upload copies of your transcripts or grades. Please note that all documentation must be in English or a Scandinavian language.

General information

The best qualified candidates will invited for interviews.

Applicant lists can be published in accordance with Norwegian Freedom of Information Act § 25. When you apply for a position with us, your name will appear on the public applicant list. It is possible to request to be excluded from this list. You must justify why you want an exemption from publication and we will then decide whether we can grant your request. If we can't, you will hear from us.

Please refer to Regulations for the Act on universities and colleges chapter 3 (Norwegian), Guidelines concerning appointment to post doctoral and research posts at UiO (Norwegian) and Regulations for the degree of Philosophiae Doctor (PhD) at the University of Oslo.

The University of Oslo has a transfer agreement with all employees that is intended to secure the rights to all research results etc.

Informasjonskapsler på arbeidsplassen.no

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