Machine Learning and Explainable AI (EPSRC iCASE studentship)
Primary supervisor
Contact admissions office
Other projects with the same supervisor
- Trust and Wellbeing in Transparent Human-Robot Interaction Teams
- Machine Learning and Robotics (Honda Scholarship)
- Explainable AI and Dialog for Trust in Human-Robot Interaction
Funding
- Directly Funded Project (UK Students Only)
This research project has funding attached. It is only available to UK citizens or those who have been resident in the UK for a period of 3 years or more. Some projects, which are funded by charities or by the universities themselves may have more stringent restrictions.
Project description
This iCase PhD project aims at the development of novel, explainable AI and machine learning models for human-machine interaction (HMI). The integration of artificial Theory of Mind (ToM) models with explainable AI methods offer the opportunity to improve trust in collaborative HMI scenarios by adding a component of "explicit" ToM building and update, to complement existing "implicit" models of intention reading. Moreover, explainable AI interaction on the machine???s decision making process can allow the interacting agents to repair their ToM, e.g. in uncertain and vague situations, and when errors are produced. These explainable ToM models can contribute to various HMI scenarios (e.g. interaction of people with collaborative robots (cobots) for joint manipulation task and interaction with virtual agents).
This is an EPSRC iCASE studentship supporting collaboration between the University of Manchester and the industrial collaboration sponsor BAE Systems. This enables us to offer the successful candidate and enhanced stipend. The studentship also includes UK home PhD fees.
The work will be carried out in the Cognitive Robotics Lab at the University of Manchester, with placement opportunities at BAE Systems. The student will be supervised by Angelo Cangelosi at the University of Manchester and by Olivia Whitehead at BAE Systems.
The student is expected to have a BSc or MSc in Computer Science, AI or allied disciplines, with minimum grade of 2.1 for BSc, have excellent programming skills (e.g. C++, Python) and possibly experience on machine learning projects.
The project is restricted to students with UK nationality.
Application Deadline: 26th February 2021.
For informal enquires, email angelo.cangelosi@manchester.ac.uk.
Person specification
For information
- Candidates must hold a minimum of an upper Second Class UK Honours degree or international equivalent in a relevant science or engineering discipline.
- Candidates must meet the School's minimum English Language requirement.
- Candidates will be expected to comply with the University's policies and practices of equality, diversity and inclusion.
Essential
Applicants will be required to evidence the following skills and qualifications.
- You must be capable of performing at a very high level.
- You must have a self-driven interest in uncovering and solving unknown problems and be able to work hard and creatively without constant supervision.
Desirable
Applicants will be required to evidence the following skills and qualifications.
- You will have good time management.
- You will possess determination (which is often more important than qualifications) although you'll need a good amount of both.
General
Applicants will be required to address the following.
- Comment on your transcript/predicted degree marks, outlining both strong and weak points.
- Discuss your final year Undergraduate project work - and if appropriate your MSc project work.
- How well does your previous study prepare you for undertaking Postgraduate Research?
- Why do you believe you are suitable for doing Postgraduate Research?