PhD Studentship in Epistemic Artificial Intelligence

Faculty of Technology Design and Environment

One 3 year full-time funded PhD Studentship

Deadline for applying: 10th October 2021

Start date: Earliest January 2022

The Faculty of TDE at Oxford Brookes University is pleased to offer a three-year full-time PhD studentship commencing January 2022, funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 964505 “Epistemic AI”.

The successful candidate will join the Visual Artificial Intelligence Laboratory under the supervision of Professor Fabio Cuzzolin . It is a fully-funded studentship with annual bursary of £16,540.

Project description

The Visual Artificial Intelligence Laboratory is a fast-growing research unit currently on a budget of £3 million from nine live projects funded by the EU (2), Innovate UK (2), the Leverhulme Trust and others. Our research interests span artificial intelligence, uncertainty theory, machine learning, computer vision, autonomous driving, surgical and mobile robotics, AI for healthcare. The Lab currently pioneers frontier topics in AI such as machine theory of mind, self-supervised learning, continual learning and future event prediction.

The PhD student will join the Lab’s work towards a new Horizon 2020 Future Emerging Technologies project “Epistemic AI ” coordinated by Prof Cuzzolin and whose other partners are TU Delft (Netherlands) and KU Leuven (Belgium). The project started in March 2021 and will conclude after 4 years.

The project’s overarching objective is to develop a new paradigm for a next-generation artificial intelligence providing worst-case guarantees on its predictions thanks to a proper modelling of real-world uncertainties. The project re-imagines AI from the foundations, aiming to provide a proper treatment of the ‘epistemic’ uncertainty stemming from a machine’s forcibly partial knowledge of the world by means of advanced uncertainty theory. All new algorithms and learning paradigms will be tested in the context of autonomous driving.

Requirements

We seek a highly competent candidate to submit their thesis within 3 years. Candidates should have a strong mathematical background, specifically in optimisation, probability and statistics, and a good first degree in Machine Learning, Artificial Intelligence or related fields. Applicants are also expected to have Research experience in Machine Learning or Artificial Intelligence, and good coding skills in Python and/or C++. Knowledge of uncertainty theory, including belief functions, random sets or imprecise probabilities is desirable, as is experience of coding in Torch, PyTorch, Tensorflow or Caffe, and experience of work in autonomous driving

How to apply

To apply, please request an application pack by emailing [email protected] , quoting “PhD Studentship in Epistemic Artificial Intelligence”. The deadline for completed applications is 10 October 2021. Please be advised that the selection processwill involve an interview.

For informal queries contact Prof Fabio Cuzzolin ([email protected] ), and Dominic Maitland ([email protected] ) should you have any questions about the application process.