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Johanna Björklund

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PhD student in Computing Science with focus on Machine Learning for Graph Transformations Umeå University in Sweden

Degree Level

PhD

Field of study

Computer Science

Funding

Available

Deadline

Nov 30, 2026

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Country

Sweden

University

Umeå University

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Keywords

Computer Science
Information Technology
Mathematics
Theoretical Computer Science
Computational Science
Reinforcement Learning
Automata Theory
Formal Languages
Search Algorithms
ML

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About this position

This PhD project at Umeå University sits in the Department of Computing Science and focuses on machine learning for graph transformations. The research aims to combine deep learning with grammatical inference to build models that are interpretable, efficient, and mathematically verifiable, while still benefiting from the flexibility of neural methods.

The project is centered on graphs as a representation of structured information, from sentences and computer programs to social networks, and on how graph-based methods can help make future generative AI systems safer and more reliable. Rather than relying on opaque heavy models, the work explores transparent, rule-based rewriting systems that can transform graphs, validate AI-generated structures, and support inference-time guidance for neural networks.

The student will investigate learning approaches that draw on grammatical inference, reinforcement learning, and efficient search algorithms to discover both rules and probabilities for complex graph behavior. The project is intended to produce research relevant to theoretical computer science and symbolic machine learning, with possible implications for automated theorem proving, knowledge-graph inference, and causal analysis.

The PhD candidate will work closely with the PI and her research group in a research environment described as inclusive, collaborative, and bottom-up driven. The department highlights rapid growth, a diverse international community, and strong support for career development, networking, and administrative and technical services.

Funding details

Available

What's required

Applicants must have a second-cycle degree, or completed course requirements of at least 240 ECTS credits with at least 60 ECTS credits at second-cycle level, or an equivalent education/qualification. For admission to doctoral studies in computer science, applicants must also have completed at least 90 higher education credits in computer science or in subjects directly relevant to the specialization. Candidates should have solid analytical and mathematical abilities, experience with machine learning, experience with formal language theory or automata theory, strong communication skills and proficiency in English, and the ability to work independently as well as collaboratively. Experience with academic writing, strong programming skills particularly in Python, familiarity with knowledge graphs, and experience with graph neural networks are advantageous.

How to apply

Prepare a complete application in English or Swedish with a cover letter, CV, thesis copies and relevant publications, degree certificates with transcripts, and documentation of other relevant experience. Submit the application electronically through Umeå University’s e-recruitment system and ensure it is received by 2026-11-30. Attach all files in PDF format.

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Professors

Professor at Umeå University

University Name
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Sweden

Research Interests

Media Studies

Gender Studies

Computer Science

Information Technology

Natural Language Processing