PhD Research Fellow in Machine Learning and Distributed Data Processing

PhD Research Fellow in Machine Learning and Distributed Data Processing

PhD Research Fellow in Machine Learning and Distributed Data Processing

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 .

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.

Whatskillsareimportantinthisrole?

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.

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 .

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.

Whatskillsareimportantinthisrole?

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 :

Language requirement :

Grade requirements :

The norm is as follows :

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

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 :

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.

We can offer you

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 :

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 doctoraland 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.

For questions about the recruitment system, please contact HR Adviser Therese Ringvold

The University of Oslo is Norway’s oldest and highest rated institution of research and education with 26 500students and 7 200employees. 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.

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