The University of Twente is pleased to announce two fully funded PhD Positions in Data-Efficient Foundation Models for Vision. These positions offer an exciting opportunity to contribute to cutting-edge research in data-efficient and robust vision foundation models.
Eligibility for these PhD positions requires applicants to hold or be close to completing a relevant master’s degree in fields such as Computer Science, Computer Engineering, Mathematics, Artificial Intelligence, or Machine Learning. Candidates should have strong skills in machine learning, computer vision, mathematics, and programming, along with good analytical and communication abilities.
Universiteit Twente Information
Founded in 1961, Universiteit Twente (University of Twente) is a non-profit public higher education institution located in the large town of Enschede (population range of 50,000-249,999 inhabitants), Overijssel. Officially accredited and/or recognized by the Ministerie van Onderwijs, Cultuur en Wetenschap, Nederland (Ministry of Education, Culture and Science, Netherlands), Universiteit Twente is a large (uniRank enrollment range: 10,000-14,999 students) coeducational higher education institution. Universiteit Twente offers courses and programs leading to officially recognized higher education degrees such as bachelor degrees, master degrees, doctorate degrees in several areas of study. See the uniRank degree levels and areas of study matrix below for further details.
Offered Benefits
• Fully funded 4-year PhD contract
• Salary from €3,059 to €3,881 per month
• 8% holiday allowance and 8.3% year-end bonus
• Participation in the Twente Graduate School training programme
• Travel budget for conferences and research events
• Minimum 232 leave hours per year + additional hours for 40-hour working weeks
• Flexible working arrangements, including partial remote work
• Free access to sports facilities on campus
• Supportive, family-friendly work environment with parental leave options
• Opportunity to work with leading researchers within an international, interdisciplinary environment.
Application Process
Interested candidates must submit their application online via the “ Apply now” button before 7 January 2026.
The application must include:
• Curriculum Vitae (max 2 pages), including publications and contact details of two references
• Cover letter (max 1 page) explaining motivation, suitability, and preferred PhD position(s)
• Academic transcripts listing all courses and grades
• Valid English language test score (if applicable)
Shortlisted candidates will be invited for interviews in early February 2026.