46 phd-studenship-in-computer-vision-and-machine-learning PhD positions at Utrecht University in Netherlands
Sort by
Refine Your Search
-
computational lens. This calls for strong expertise in computational methods, machine learning, and data modelling combined with solid knowledge of music. We particularly aim to cover a broad range of musical
-
PhD Position in Categorical Foundations of Type Theory Faculty: Faculty of Science Department: Department of Information and Computing Sciences Hours per week: 36 to 40 Application deadline: 6
-
PhD Money in postdivorce families: Resource pooling and transfers to children Faculty: Faculty of Social and Behavioural Sciences Department: Social Sciences Hours per week: 36 to 40 Application
-
the project develops. During the PhD, you will: Gain expertise in theory-driven empirical sociology Learn to derive hypotheses from deductive theoretical reasoning through formal methods on sociological
-
PhD Position in Nutritional Immunology Faculty: Faculty of Science Department: Department of Pharmaceutical Sciences Hours per week: 36 to 40 Application deadline: 29 March 2026 Apply now Within
-
on behavioral lab experiments but may also include other empirical approaches depending on how the project develops. During the PhD, you will: Learn how to combine theory-driven empirical sociology with
-
PhD: The Effects of Polarization Panic and Migration on Social Cohesion Faculty: Faculty of Social and Behavioural Sciences Department: Psychology Hours per week: 36 to 40 Application deadline
-
PhD Position in Explainable AI for High-Stake Decision Making Faculty: Faculty of Science Department: Department of Information and Computing Sciences Hours per week: 36 to 40 Application
-
PhD in the economic aspects of water-resilient landscapes Faculty: Faculty of Law, Economics and Governance Department: Utrecht University School of Economics Hours per week: 36 to 40 Application
-
into the PhD programme. Required qualifications: Demonstrated experience with experimental techniques (e.g., flow-through experiments, column studies, material characterization) and/or numerical modeling of flow