Overview
This is a unique opportunity for a motivated PhD student to join the Department of Electronic & Electrical Engineering at University College London (UCL). Funded by the UCL EPSRC Landscape Award (UELA), this position focuses on the intersection of causality, network science, and generative AI, aiming to develop intelligent systems that can comprehend the underlying reasons behind events in complex networks, such as power grids and climate systems.
Background & Relevance
Causal AI and Graph Generative Models are pivotal in understanding complex systems. By analyzing how different elements interact within networks, researchers can gain insights into system resilience and decision-making processes. This research is crucial as it addresses real-world challenges, including sustainability and optimization in infrastructure systems, which are increasingly vital in today’s context of climate change and resource management.
Key Details
- Project Title: Causal Inference and Generative Models in Dynamic Processes to Analyze and Enhance Resilience in Complex Networks.
- Funding Source: UCL EPSRC Landscape Award (UELA).
- Stipend: Approximately £23,466 per year (tax-free).
- Eligibility: Fully funded for Home students; International applicants can apply, but places are limited.
- Application Deadline: Monday, 05 January 2026.
- Application Link: UCL EPSRC Landscape Award Studentships
Eligibility & Participation
This PhD position is targeted at candidates with a robust academic background in Mathematics, Statistics, Optimization, or Machine Learning. Proficiency in Python is essential. The ideal candidate should be eager to tackle significant AI challenges related to Causal Inference and Graph Learning, with a focus on real-world sustainability impacts.
Submission or Application Guidelines
Interested candidates should contact Dr. Laura Toni to express their interest. It is advised to avoid generic emails and to briefly explain how their background aligns with the project’s focus areas. The application process involves multiple steps, starting with the submission of “Part A” online before the deadline to receive links for the complete application.
More Information
This research fits into the broader context of AI and ML by addressing critical issues in understanding complex systems. The integration of Causal Inference and Generative Models can lead to innovative solutions for enhancing resilience in various infrastructures, making this an impactful area of study.
Conclusion
This PhD position at UCL presents an exciting opportunity for those interested in advancing their research in Causal AI and Graph Generative Models. Prospective candidates are encouraged to apply and contribute to meaningful advancements in the field.
Category: PhD & Postdoc Positions
Tags: causal ai, graph generative models, ucl, machine learning, network science, causal inference, dynamic processes, sustainability, optimization, electronic engineering, data science, python
