Umeå University is inviting applications for a fully funded PhD student in Computing Science with a focus on Machine Learning for Graph Transformations. This doctoral research project explores a hybrid framework that bridges deep learning with grammatical inference, aiming to create interpretable, verifiable, and mathematically sound AI systems for graph-based structures.
Overview of the Position
| Detail | Information |
|---|---|
| Designation | PhD Student / Doctoral Researcher |
| Institution | Umeå University |
| Department | Department of Computing Science |
| Location | Umeå, Sweden |
| Employment Type | Full-time, Temporary (4 to 5 years) |
| Research Area | Machine Learning, Graph Transformations, Symbolic AI, Theoretical Computer Science |
| Application Deadline | November 30, 2026 |
Research Area
The position is rooted in theoretical computer science and symbolic machine learning. Graphs serve as essential representations of structured data across various domains, ranging from code and natural language to knowledge networks. As generative AI expands beyond pure text, establishing rigorous mechanisms that verify and guide outputs is critical. This project focuses on automatically learning transparent, rule-based graph rewriting systems using grammatical inference, reinforcement learning, and efficient search algorithms to provide mathematically verifiable alternatives to black-box neural networks.
Scholarship & Position Description
The successful applicant will pursue doctoral studies leading to a PhD in Computing Science under the supervision of Professor Johanna Björklund. Key aspects of the position include:
- A standard duration of four years of full-time doctoral studies (100%).
- Possibility to extend up to five years if departmental duties, such as teaching, are included (up to a maximum of 20%).
- Employment is provided under Swedish university regulations with standard doctoral student salary and full social benefits.
- Access to career development support, a collaborative international workplace, and cutting-edge research facilities.
- Expected starting date: January 12, 2027, or as mutually agreed.
Eligibility and Qualifications
General and Specific Requirements
- A completed second-cycle degree (Master’s level), or completion of at least 240 ECTS credits (with at least 60 ECTS credits at second-cycle level), or equivalent foreign qualification.
- At least 90 higher education credits in computer science or closely relevant subjects.
- Solid analytical and mathematical abilities.
- Demonstrated experience in machine learning.
- Familiarity with formal language theory or automata theory.
- Strong command of English, both written and oral, along with effective collaboration and communication skills.
Meritorious Qualifications
- Proficiency in programming, particularly with Python.
- Experience with academic writing and publishing.
- Prior exposure to knowledge graphs and graph neural networks (GNNs).
- Strong self-motivation, intellectual curiosity, and organizational skills.
How to Apply
Applications must be submitted electronically through Umeå University’s official e-recruitment portal. Documents must be in English or Swedish and uploaded in PDF format:
- A cover letter detailing your research interests, reasons for applying, and contact information.
- A detailed Curriculum Vitae (CV).
- Copies of completed Bachelor’s and/or Master’s theses and other relevant publications (if applicable).
- Degree certificates and complete academic transcripts reflecting completed coursework and grades.
- Documentation highlighting any other relevant skills or professional experience.
Last Date for Apply
The deadline to submit your application is November 30, 2026.
Apply Link
For further details and to submit your application online, visit the official application portal: Apply for PhD Student in Computing Science at Umeå University.
