Research Fellow, Citizen-Centric AI Systems
- Full Time
Agents, Interactions & Complexity
Location: Highfield Campus
Salary: £30,942 to £33,797 - per annum
Full Time Fixed Term (for 36 months)
Closing Date: Sunday 11 April 2021
Interview Date: See advert
You will work on an exciting new project on citizen-centric AI systems. This project is funded via a prestigious £1.4M UKRI Turing AI Acceleration Fellowship that supports world-leading AI research.
The vision of this project is to develop AI systems with people at their heart. These citizen-centric AI systems learn the preferences of individual users to provide personalised services and advice in important application areas such as smart transportation, energy and disaster response. To ensure trustworthiness, these systems safeguard privacy by learning and making decisions locally, for example on a user's smart device.
You will design fundamental algorithms and models for learning the preferences of users, using techniques such as interactive preference elicitation and inverse reinforcement learning. You will validate your approaches on real-world data sets and in trials with end users.
The project has the strong support of a unique consortium of industrial stakeholders, including companies such as IBM Research, Siemens Mobility, EA Technology, Dstl, UTU Technologies and Thales. These will interact with you regularly to ensure your work will help address real societal challenges. Such interactions will include regular meetings, workshops, as well as work on joint papers and potentially secondments.
To be successful you will have (or be within 6 months of completing) a PhD (or equivalent professional qualifications and experience) in computer science or artificial intelligence or multi-agent systems or human-computer interaction. You have the ability to publish and present your work at top international venues, and you are passionate about working with stakeholders and end users to generate real impact from your research.
Ideally, your PhD is in an area closely aligned with citizen-centric AI systems, for example in human-AI interaction, preference modelling/elicitation, explainable AI or reinforcement learning. It is also desirable for you to have some experience evaluating AI systems with users. You are ideally available to work from June 2021, although there is some flexibility in the exact starting date.
Applications will be considered from candidates who are working towards or nearing completion of a relevant PhD qualification. The title of Research Fellow will be applied upon completion of PhD. Prior to the qualification being awarded the title of Senior Research Assistant will be given.
This role will be offered on a full time, fixed term basis for 36 months.
Interviews are scheduled to commence between 23-30 April 2021.
You will join the Agents, Interaction and Complexity research group within the School of Electronics and Computer Science (ECS) at Southampton. We are one of the world's leading groups in multi-agent systems research, and you will benefit from our significant research networks. For example, we lead the UKRI Trustworthy Autonomous Systems Hub, we are a member of the Alan Turing Institute, and we run the MINDS CDT. These centres and networks will provide you with a valuable opportunity to work with researchers and other stakeholders from a wide range of backgrounds and disciplines.
We highly value diversity in our teams, and we particularly encourage women, Black, Asian and minority ethnic (BAME), LGBT+ and disabled applicants to apply for this position. ECS is committed to Equality, Diversity and Inclusion, and we hold an Athena SWAN Bronze Award. We give full consideration to applicants who wish to work flexibly and those who have taken a career break. The University has a generous maternity policy (subject to qualifying criteria) and onsite childcare facilities.
For informal enquiries about this position, please contact Dr Sebastian Stein (firstname.lastname@example.org).
You should submit your completed online application form at https://jobs.soton.ac.uk. The application deadline will be midnight on the closing date stated above. If you need any assistance, please call Dan Ward (HR Recruitment Team) on 02380 592750 or email email@example.com Please quote reference 1346021FP on all correspondence.