PhD Computing Science: Explainable and trustworthy human-machine collaboration in oilfield drilling

Many future industrial operations will be carried out by teams consisting of humans and machines. In this project, the student will investigate how human-machine trust and explainable/transparent artificial intelligence affect such human-machine collaborative tasks. The work will concentrate on the communication aspects: how the machine communicates its intentions and reasoning processes to the human, and how the human can query and interact with the robot’s plan.

The project will be driven by oilfield drilling applications, which involve control of complex equipment in a dynamic environment, with an increasing level of automation. In this setting, close coordination and trust between the human crew and the automation system is required: the crew must both understand why the machine acts the way it does, as well as be confident it has taken all available information into account.

The student will be based in the School of Computing Science and will be part of the Glasgow Social Robotics initiative, which is a collaboration between Computing Science and Psychology.

The student should have excellent experience, enthusiasm and skills in the areas of artificial intelligence and/or automated planning and reasoning and/or natural language or multimodal interaction. Applicants must hold a good Bachelor’s or Master’s degree in a relevant discipline.

The project is an EPSRC iCASE award with Schlumberger Gould Research and it is expected that the student will spend some time working with the company in Cambridge. This will give you a great opportunity of working in an internationally excellent research group as well as a leading player in the oil and gas industry. Travel and accommodation costs will be paid during the time at Schlumberger.