PhD position Compositionality Computer Vision

Job description

The Data Management and Biometrics (DMB) group at the University of Twente is seeking one PhD candidate to join the research team of Dr. Nicola Strisciuglio to work on compositional learning for data-efficient vision foundation models.

Foundation models in computer vision currently rely on massive datasets and brute-force scaling. This leads to high data requirements, hidden biases, limited accessibility, and dependency on corporate-controlled resources. The project aims to develop data-efficient and reliable training strategies for vision foundation models, reducing the need for large datasets and improving robustness.

The project will explore strategies related to
1) Object-attribute compositionality to replace exhaustive data requirements with structured concept learning,
2) Bias detection and machine unlearning to identify and mitigate bias and shortcuts early in training, and
3) Perceptual and conceptual priors to design self-supervised objectives that capture continuous similarity rather than binary contrastive notions.

By embedding compositional structure and prior knowledge into the training process, the project aims to break the dependency on uncontrolled large-scale datasets and enable broader, more transparent development of vision foundation models.

We offer one fully funded 4‑years PhD position, in the context of the project described above, with specific focus on the topic of Compositional Learning for Vision Foundation Models. The aim will be to explore compositional learning strategies (e.g. attribute-object visual representation, or other forms) to reduce the data requirements to train vision foundation models.

You are required to clearly motivate why you are a good fit for this position and how your expertise and previous experience match the position topic.

• You have (or will shortly acquire) a master’s degree in the field of Computer Science, Computer Engineering, or Mathematics with a major in Artificial Intelligence, Machine Learning, or Computer Vision.
• Background in machine learning, particularly in computer vision, solid understanding of mathematics and excellent programming skills.
• An interest in research and developing creative solutions to advance compositional learning and data efficiency of Foundation Models for vision.
• A creative mindset and excellent analytical and communication skills.
• A good team spirit and like to work in an interdisciplinary and internationally oriented environment.
• Proficiency in English.
• Previous experience in scientific publishing (at top venues like CVPR, ICCV, ECCV, ICLR, etc.) is appreciated.

• A full-time position for four years, with a qualifier in the first year, and the flexibility to work (partially) from home.
• Your salary and associated conditions are in accordance with the collective labour agreement for Dutch universities (CAO-NU).
• You will receive a gross monthly salary ranging from €3,059 (first year) to €3,881 (fourth year).
• There are excellent benefits including a holiday allowance of 8% of the gross annual salary, an end‑of‑year bonus of 8.3%, and a solid pension scheme.
• A minimum of 232 leave hours in case of full-time employment based on a formal workweek of 38 hours. A full‑time employment in practice means 40 hours a week, therefore resulting in 96 extra leave hours on an annual basis.
• Free access to sports facilities on campus.
• A family‑friendly institution that offers parental leave (both paid and unpaid).
• You will have a training programme as part of the Twente Graduate School where you and your supervisors will determine a plan for a suitable education and supervision, and a travel budget to attend conferences and scientific events.

For more information regarding this position, you are welcome to contact Dr. Nicola Strisciuglio (n.strisciuglio).

The first round of interviews will be held during the second half of August 2026.