PhD Studentship in Explainable AI, Knowledge Representation and Machine Learning

Applications are invited for a PhD position in Artificial Intelligence, to be based in the School of Informatics at the University of Edinburgh. The position is an opportunity to combine cutting-edge research at the intersection of knowledge representation and machine learning, in service of enabling explainability in AI, and yield interpretable decision-making models.

Technical themes of interest include (but are not limited to):

-probabilistic inference and learning
-probabilistic programming and program induction
-statistical relational learning
-commonsense reasoning and learning
-multi-agent learning and decision-making
-combinations thereof involving natural language understanding and human-machine interaction

The project is suitable for a student with a top MSc or first-class bachelor’s degree in computer science, mathematical logic, statistics, physics, or a related discipline.

Previous coursework or experience in machine learning, statistical natural language processing, and programming languages is desirable, although we do not expect students to have all three of these. Because of the scale of the data sets involved, a strong programming background will be essential for this project.

For informal enquiries about the position, please contact Vaishak Belle: [Email Address Removed] with a short summary of your background and research interests in the technical themes mentioned above. (No attachments please.)

Formal application must be through the School’s normal PhD application process (opting for the CISA institute)

http://edin.ac/2zrENJx