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Research Associate/Fellow Lifelong AI Safety

University of York - Computer Science

Location: York
Salary: £36,024 to £54,395 per annum
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 22nd February 2024
Closes: 20th March 2024
Job Ref: 13136

Role Description

Department

This role will give you the opportunity to advance state-of-art and empirical research in safe Artificial Intelligence (AI) and Autonomous Systems (AS) in a range of application domains including autonomous driving and healthcare. You will be key to establishing a new Centre, building on the work of the Assuring Autonomy International Programme (AAIP), which pioneered approaches to assuring autonomous systems and their machine learning (ML) components.

Role

You will be researching techniques for ensuring that ML systems are acceptably safe, and importantly, continue to be acceptably safe after their deployment. This will cover issues of retraining, continual learning and/or transfer learning and how to assure the safety of these approaches in critical applications. Topics of interest include monitoring, out-of-distribution detection and explainability. You will explore the notion of dynamic safety cases and the need for the safety justification and evidence to evolve in response to changes in the world or our understanding of the system.

This is an inherently interdisciplinary research area and will require you to work closely and effectively with other team members and be able to explain your research clearly and precisely. You will evaluate your research through in-depth case studies, requiring close collaboration with industrial and regulatory partners.

Skills, Experience & Qualification needed

  • First degree in Computer Science, Engineering, or cognate discipline
  • PhD in Computer Science, Engineering, or equivalent experience
  • Knowledge of machine learning or data science as applied to real-world applications
  • Knowledge of safety analysis or safety cases
  • Knowledge of transfer learning and/or continual learning
  • Competency in training and testing machine learning models
  • Experience of developing and testing machine learning models
  • Ability to work as part of a diverse and multidisciplinary team

Interview date: to be confirmed

For informal enquiries: please contact Professor Ibrahim Habli on ibrahim.habli@york.ac.uk

The University strives to be diverse and inclusive – a place where we can ALL be ourselves.

We particularly encourage applications from people who identify as Black, Asian or from a Minority Ethnic background, who are underrepresented at the University.

We offer family friendly, flexible working arrangements, with forums and inclusive facilities to support our staff. #EqualityatYork

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