Oxford Brookes University

Faculty of Technology Design and Environment

School of Engineering, Computing and Mathematics

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1 three-year full-time funded PhD Studentship

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Eligibility: all students

Bursary: ��16,540 per year

Fees: Tuition fees will be paid by the university

Deadline for applying: 10th October 2021

Start date: Earliest January 2022

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The Faculty of TDE at Oxford Brookes University is pleased to offer a three-year full-time PhD studentship to a student 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 PhD studentship with annual bursary of ��16,540.

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Project description

The Visual Artificial Intelligence Laboratory is a fast-growing research unit currently running 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 is currently pioneering 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 FET (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 has a duration of 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, with the aim of providing 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 are to be tested in the context of autonomous driving.

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Requirements

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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

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How to apply

To apply, please please go directly to the university here: https://www.brookes.ac.uk/studying-at-brookes/how-to-apply/applying-direct/, quoting ��PhD Studentships in Epistemic Artificial Intelligence��.

Fully completed applications must be submitted online by 10th October 2021. As part of the application process you must submit your CV, a Research Proposal (two pages), copies of your current degrees and transcripts, IELTS (if applicable), and a supporting statement (2-page maximum) which explains why you believe you are the best candidate for this studentship. Please be advised that the selection process may involve an interview.

For informal requests contact Prof Fabio Cuzzolin (fabio.cuzzolin@brookes.ac.uk), and Dominic Maitland (tdestudentships@brookes.ac.uk) should you have any questions about the application process.