PhD Research Fellow in Machine Learning and Distributed Data Processing
Deadline: 25.09.2025
Publisert
The University of Oslo is Norway’s oldest and highest rated institution of research and education with 26 500 students and 7 200 employees. Its broad range of academic disciplines and internationally esteemed research communities make UiO an important contributor to society.
The Department of Informatics (IFI) is one of nine departments belonging to the Faculty of Mathematics and Natural Sciences. IFI is Norway’s largest university department for general education and research in Computer Science and related topics.
The Department has more than 1800 students on bachelor level, 600 master students, and over 240 PhDs and postdocs. The overall staff of the Department is close to 370 employees, about 280 of these in full time positions. The full time tenured academic staff is 75, mostly Full/Associate Professors.
Job description
Position as PhD Research Fellow in Machine Learning and Distributed Data Processing is available at the Department of Informatics, University of Oslo.
Starting date preferably no later than 17.11.2025.
The position is in the context of a new project, funded by the Research Council of Norway, called Scalable Sustainability with Condensed and Expanded Digital Product Passports (SecondPass).
The fellowship period is three years and devoted to carrying out research in the context of the SecondPass project. The research is conducted in collaboration with Norwegian Institute for Sustainability Research (NORSUS), University of Manchester (UK), and University of Leiden (Netherlands).
Depending on the candidate and the teaching needs of the department, the fellowship period can be extended for either for compulsory work consisting of e.g., teaching and supervision duties and research assistance up to four years.
Place of work is the Department of Informatics at Blindern, Oslo.
No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo.
More about the project and PhD position
The European Commission, under its Green Deal initiative, has introduced the concept of Digital Product Passports (DPPs) as a key enabler of circular business models, aiming to reduce CO₂ emissions and improve resource efficiency through enhanced data-driven lifecycle management. A DPP can be viewed as a structured, machine-readable knowledge artifact that captures heterogeneous information across the entire product lifecycle to support sustainable decision-making. Functioning as a data backbone for the circular economy, DPPs integrate numerical, categorical, textual, and often multilingual content (i.e., multimodal), spanning diverse sectors such as consumer goods, electronics, and healthcare. From a computational perspective, DPPs represent a large-scale, dynamic, and heterogeneous data integration problem, where challenges include missing or noisy data, redundancy across sources, dynamic updates, and the need for robust semantic alignment and interoperability across distributed ecosystems.
The SecondPass project addresses these challenges by advancing machine learning (ML)-based and data-intensive methods for the scalable design, processing, and deployment of DPPs.
The advertised PhD position focuses on developing ML-based and distributed data processing approaches to address issues of incomplete or redundant multimodal data, dynamic updates, and scalable semantic interoperability in large-scale DPP systems. Particular emphasis will be placed on Representation Learning techniques, Transformer-based architectures, Large Language Models (LLMs), Natural Language Processing (NLP), etc. The research will also explore distributed data processing frameworks to ensure robustness, interoperability and scalability in DPP-based information systems.
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:
Applicants must hold a Master’s degree or equivalent in Computer Science or Information Technology
Foreign completed degree (M.Sc.-level) corresponding to a minimum of four years in the Norwegian educational system is required
The candidate must have interest and solid background in software systems, machine learning, and distributed systems.
The candidate should have relevant scientific publications, showcasing research interest and experience in the core areas of the position
The candidate must be proficient in Python, C++ or Java and familiar with relevant programming frameworks and tools (e.g., PyTorch and TensorFlow)
Fluent oral and written communication skills in English
Desired qualifications:
It is desirable that the candidate has good knowledge on transformers, natural language processing (NLP), LLMs, and distributed data processing
The ideal candidate should possess strong analytical and problem-solving skills
It is desirable to have experience in working on interdisciplinary projects
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
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
The purpose of the fellowship is research training leading to the successful completion of a PhD degree. For more information see here.
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.
What are we looking for in you?
Personal skills:
Ability to work precise in a structured manner and swiftly adapts to new tasks
Positive attitude and the ability to handle hectic periods
The evaluation considers many aspects of personal qualifications, including organizational skills, strong communication skills, motivation and commitment, and the ability to collaborate effectively in a team-oriented, international research environment.
Employment in the position is based on a comprehensive assessment of all qualification requirements applicable to the position, including personal qualifications.
Membership in the Statens Pensjonskasse, which is one of Norway's best pension schemes with beneficial mortgages and good insurance schemes
Oslo’s family-friendly surroundings with their rich opportunities for culture and outdoor activities
Salary in position as PhD Research Fellow, position code 1017 in salary range NOK from 550 800 - 595 000, 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.
How to apply
The application must 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
Copies of 2-3 letters of recommendation
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.
Questions about the position
Amir Taherkordi (Professor), amirhost@ifi.uio.no
Ingrid Chieh Yu (Associate Professor), ingridcy@ifi.uio.no
For questions about the recruitment system, please contact:
