2 PhD positions on Data-Efficient Foundation Models for Vision
Are you passionate about Computer Vision and Machine Learning? We offer two challenging PhD positions in the group Data Management and Biometrics, in the team of Nicola Strisciuglio, to develop new techniques for compositional learning and data efficiency of Vision Foundation Models.
The Data Management and Biometrics (DMB) group at the University of Twente is seeking two PhD candidates to join the research team of Dr. Nicola Strisciuglio for the NWO-VIDI project “ReVision: Robust and Data-Efficient Vision Foundation Models”.
About the project - ReVision
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. ReVision 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 structure and prior knowledge into the training process, ReVision aims to break the dependency on uncontrolled large-scale datasets and enable broader, more transparent development of vision foundation models.
About the PhD positions:
We offer two fully-funded 4-years PhD positions, with specific focus on Compositional Learning (PhD position 1) and Self-supervised Learning with priors (PhD position 2). The ReVision team will share efforts on integrating machine unlearning techniques to remove biases and shortcuts during model training.
While applying, you are asked to motivate the choice of (one or both) the position(s) you are applying for.
Information and application
Are you interested in this position? Please send your application via the 'Apply now' button below before January 7, 2026, and include:
- A Curriculum Vitae (max 2 pages A4), including, and, if applicable, a list of publications, and the contact details of two academic references.
- A cover letter (maximum 1 page A4), emphasising your specific interest for the project, and qualifications and motivations to apply for one of the two (or both) available PhD positions.
- An academic transcript with the list of all courses attended and grades you obtained.
- An IELTS-test, Internet TOEFL test (TOEFL-iBT), or a Cambridge CAE-C (CPE). Applicants with a non-Dutch qualification and who have not had secondary and tertiary education in English can only be admitted with an IELTS-test showing a total band score of at least 6.5, internet. TOEFL test (TOEFL-iBT) showing a score of at least 90, or a Cambridge CAE-C (CPE).
For more information regarding this position, you are welcome to contact Dr. Nicola Strisciuglio (n.strisciuglio@utwente.nl).
The first round of interviews will be held during the first (full) week of February 2026.
Screening is part of the selection process.
About the organisation
The faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) uses mathematics, electronics and computer technology to contribute to the development of Information and Communication Technology (ICT). With ICT present in almost every device and product we use nowadays, we embrace our role as contributors to a broad range of societal activities and as pioneers of tomorrow's digital society. As part of a tech university that aims to shape society, individuals and connections, our faculty works together intensively with industrial partners and researchers in the Netherlands and abroad, and conducts extensive research for external commissioning parties and funders. Our research has a high profile both in the Netherlands and internationally. It has been accommodated in three multidisciplinary UT research institutes: Mesa+ Institute, TechMed Centre and Digital Society Institute.
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