PhD position in Causal AI

13 ago - Italia
IIT-CNR

A fully funded 3-year Ph.D. position in Causal AI within the National PhD AI Program at the University of Pisa (Italy) is sponsored by the Ubiquitous Internet (UI) research group of IIT-CNR. We are looking for a highly motivated Ph.D. candidate with a strong academic background to join our research team and work on this Ph.D. topic under our supervision.
The call is now open This is a scouting notice to raise awareness: the University of Pisa has officially opened Ph.D. admissions, and applications are now being accepted.
Traditional machine learning approaches primarily focus on correlation-based learning, identifying statistical associations between variables. Shifting from correlations to causal relationships is one of the most promising directions toward AI that is more robust, interpretable, and useful in practice. This research explores how heterogeneous devices (smartphones, wearables, IoT sensors, and edge systems) can be used as a substrate for causal learning in the wild. The idea is to leverage data naturally collected from distributed, device-rich environments (smartphones,



wearables, and IoT sensors) as a substrate for causal learning frameworks that can extract causal knowledge from observational data in real-world setting.
Research Focus & Methodology
The target applications focus on pervasive systems, where the heterogeneity and scale of device-generated data create both unique challenges and opportunities for causal reasoning. In these settings, causal knowledge can play a key role in improving decision-making and adaptive behavior — for instance, enabling systems to generalize across different devices and environments, act robustly under uncertainty, or understand the consequences of their actions rather than merely reacting to observed patterns. Depending on the background and interests of the candidate, research activities may include:
- Theoretical modeling of causal inference in (distributed) AI settings.
- Algorithm and system design for deplo

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