This is a 2-year research post at post-doctoral level, joining a team of other research associates and investigators to work on an EPSRC/UKRI funded project THuMP: Trust in Human-Machine Partnerships. This post is focussed particularly on data visualisation.
THuMP is a multi-disciplinary project, with the ambitious goal of advancing the state-of-the-art in trustworthy human-AI decision-support systems. ThUMP will address the technical challenges involved in creating explainable AI (XAI) systems, with a focus on Visualization for Explainable Planning and Argumentation, so that people using the system can better understand the rationale behind and trust suggestions made by an AI system. This project is conducted in collaboration with three project partners: Schlumberger and Save the Children, which provide use cases for the project, and the law firm Hogan Lovells, which will cooperate in considering legal implications of enhancing machines with transparency and the ability to explain.
The candidate will be responsible for conducting research around the use of visualization to support explainability in the context of decision making in human-machine teams, particularly for resource allocation. Tasks will involve designing new visual layouts, building visual analytics software infrastructure for the project, developing a prototype interface for communicating with users, designing and conducting experiments with human subjects based on the use cases that will be co-created with the project partners, with an emphasis on resource allocation in critical domains.
This post will be offered on a fixed-term contract for 21 months.
This is a full-time post.
The selection process will include an assessment and a panel interview.
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