PhD Research Fellow in the Information-Flow Analysis for Digital Twins

About the position

Position as PhD Research Fellow in information-flow analysis for digital twins using programming language theory is available at the Department of Informatics.

No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo. Starting date no later than October 1, 2025.

The fellowship period is three (3) years.

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 needs of the department.

Job description

This position is funded by the Department of Informatics and will be part of the collaboration between the Reliable Systems (PSY) research group, which works in formal methods, programming language theory and digital twins, and the Data and Knowledge Management (DKM) research group, which works in sematic technologies. Both groups have a dynamic and interactive working environment with good gender balance, consisting of full-time professors, researchers, and many postdocs and PhD candidates.

Information-flow analysis is a technique that can be used to keep track of the flow of information within a system to ensure that the information is properly used according to some established policy or contract, giving the opportunity to identify e.g., unauthorized access to sensitive data that has potential to harm an individual, organization, or government. Access control to sensitive data, which determine who can access such sensitive data, typically requires measurements related to privacy and security because the disclosure or misuse or sensitive data could potentially lead to risks such as identity theft, financial loss, reputational damage, or legal consequences.

A digital twin is a virtual representation of a system that is continuously updated with real-time data to simulate, predict, or analyse the performance or behaviour of the twinned system. Digital twins rely heavily on data to maintain its operations, this includes both real-time data and historical data, some of which can be highly sensitive.

The planned PhD research topic will explore techniques to handle sensitive data (such as information-flow analysis) in digital twins. To explore and investigate this topic, the project will combine formal methods, programming language theory and semantic technologies, aiming to develop systematic techniques for sensitive data handling that can be integrated within a digital twin framework, e.g., a digital twin for a hospital, handling personal data according to GDPR. The PhD project aims at demonstrating the results by either a theoretical framework or in an experimental proof of concept that can be integrated to the existing digital twin framework SMOL.

Qualification requirements

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.

• Master’s degree or equivalence in a relevant field of computer science or informatics for this position, such as programming language theory, formal methods or semantic technology.
• A solid documented background in theoretical computer science is required
• Foreign completed degree (M.Sc.-level) corresponding to a minimum of four years in the Norwegian educational system
• Fluent oral and written English communication skills

Candidates without a master’s degree have until 30 June 2025 to complete the final exam.

Desired qualifications:

• Good knowledge in programming language theory, algorithms, distributed systems and logic
• Experience with language-based techniques for information-flow analysis or access control, formal methods or semantic technologies will be considered an advantage when candidates are ranked

Grade requirements:

• 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

Language requirements:

• Fluent oral and written communication skills in English

English requirements for applicants from outside of EU/EEA/EFTA countries and exemptions from the requirements

The purpose of the fellowship is research training leading to the successful completion of a PhD degree. For more information see here.

Personal skills

• Strong analytical skills
• Independent thinking, creativity and good at taking initiative
• Good communication and interpersonal skills

We offer

• Salary NOK 536 200 – 575 400 per year depending on qualifications and seniority as PhD Research Fellow (position code 1017). 
• Attractive welfare benefits and a generous pension agreement
• Vibrant international academic environment
• Career development programmes.
• Oslo’s family-friendly surroundings with their rich opportunities for culture and outdoor activities

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.

How to apply

The application must include:

• Cover letter - statement of motivation and research interests
• CV (summarizing education, positions and academic work - scientific publications)
• A statement of research interests indicating why this PhD topic fits their interest/background is required. The statement should not exceed one page
• Copies of the original Bachelor and Master’s degree diploma, transcripts of records
• Documentation of English proficiency
• List of publications and academic work that the applicant wishes to be considered by the evaluation committee
• Names and contact details of 2-3 references (name, relation to candidate, e-mail and telephone number)

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 original transcripts or grades. Please note that all documentation must be in English or a Scandinavian language. Foreign applicants should attach an official explanation of their University's grading system.

The application with attachments must be delivered in our electronic recruiting system (please follow the link “Apply for this job”). 

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.

Contact persons

For further information please contact:

• Associate Professor Silvia Lizeth Tapia Tarifa, e-mail: sltarifa@ifi.uio.no, phone: +4722840852

For questions regarding the recruitment system Jobbnorge, please contact HR Adviser Therese Ringvold, e-mail: therese.ringvold@mn.uio.no

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