Faculty: Faculty of Science
Level: Master’s
Application Deadline: 20-04-2026
Vacancy Number: 14893
Salary: €3.059 – €3.881
Are you interested in improving the interpretability, robustness, and safety of AI by integrating causal reasoning?
The Causality team in the AMLab group at the University of Amsterdam is looking for 2 PhD students to work on the NWO VIDI sponsored project CANES (CAusal NEuro-Symbolic approach to integrating perception and abstract reasoning) led by prof. Sara Magliacane.
The project aims to develop a theoretically principled framework for safe, interpretable, and robust AI by integrating perception and reasoning through causality. You will learn Causally Grounded Concepts from unstructured data with theoretical guarantees, even in challenging settings with continuous and discrete valued concepts, correlations between concepts, and weak supervision signals.
Both PhD positions belong to the same project but have independent research directions:
Project 1 – Discrete Concepts: Focus on developing strong theoretical guarantees for dependent and discrete concepts.
Project 2 – Weak Supervision: Focus on integrating background knowledge and weak supervision (e.g., labels in downstream tasks) to provide similar guarantees.
Develop methods to learn concepts from unstructured data with theoretical guarantees
Conduct machine learning research integrating causal reasoning
Choose between two projects with autonomy, contributing to a shared framework
Optionally perform a 6–12 month research visit at the Saarland Informatics Campus in Saarbrücken, Germany
Invent, evaluate, and describe novel algorithms
Present research results at international conferences, workshops, and journals
Pursue and complete a PhD thesis within 4 years
Assist in teaching activities and supervise bachelor or master students
MSc in Artificial Intelligence, Statistics, Computer Science, or a related field
Strong background in machine learning and/or statistics
Preferred prior knowledge/experience with causality, explainable AI, and/or neurosymbolic approaches
Temporary contract for 38 hours per week for 4 years
Initial contract: 18 months
Extension to full 4 years after satisfactory evaluation
Preferred start date: October 2026
Gross monthly salary: €3,059 – €3,881 (scale P), based on 38 hours per week, depending on experience
Additional 8% holiday allowance and 8.3% year-end allowance
Possible eligibility for the 30% ruling for non-Dutch applicants
Employment under the Collective Labour Agreement of Universities of the Netherlands
Educational plan including courses, meetings, and teaching responsibilities
Opportunity for international research visit (Saarland Informatics Campus)
You will work within the Amsterdam Machine Learning Lab (AMLab) at the Informatics Institute (IvI). AMLab conducts research in machine learning, AI, and applications to large-scale data domains, including:
Deep generative models
Approximate inference and probabilistic programming
Bayesian deep learning and causal inference
Reinforcement learning
Graph neural networks and geometric deep learning
You will join the Causality team, supervised by prof. Sara Magliacane, with potential research collaboration at the Saarland Informatics Campus in Germany.
The University of Amsterdam (UvA) is ambitious, creative, and committed. Founded in 1632, it is the largest university in the Netherlands with:
42,000 students
6,000 staff
3,000 PhD students
UvA is an intellectual hub fostering curiosity and innovation.
Applications must include:
Detailed CV (including months of education and work experience)
Letter of motivation, including suitability for the position and preference for one of the two projects
Writing sample in English (e.g., master thesis draft or paper)
Complete record of Bachelor and Master courses with grades and grading explanation
Names and email addresses of two references (letters not required at application stage)
Note: All files except your CV should be submitted as a single PDF document.
Deadline: 20 April 2026
Knowledge security check: May be required (national guidelines)
Contact:
Sara Magliacane, Assistant Professor – [email protected]
UvA maintains an equal opportunities policy. We value diversity and encourage all qualified candidates to apply, even if they do not meet 100% of the requested experience.
In your application, please refer to Polytechnicpositions.com