Research & Innovation Associate or Fellow in Safe MLOps

You will join an exciting new research centre in the Department of Computer Science at the University of York. The Centre for Assuring Autonomy (CfAA) is building on the work of the Assuring Autonomy International Programme (AAIP) which pioneered approaches to assuring autonomous systems and their machine learning (ML) components. The CfAA also contributes to the assurance pillar of the Institute for Safe Autonomy (ISA). You will be based at the University, in ISA, and be part of a team dedicated to delivering research projects in close collaboration with industrial partners from a number of sectors including maritime, automotive, healthcare, and robotics. This is an exciting opportunity to undertake cutting edge research and drive innovation in the safety of machine learning (ML) used in real-world applications. You will have a unique opportunity to develop and validate these techniques on real robotic and autonomous systems working with a range of industrial and regulatory collaborators. At Grade 6, you will research methods for demonstrating that ML-based functions are sufficiently safe to deploy and remain in operation as the environment and operational profiles evolve. At Grade 7, you will be expected to lead the development of methods for demonstrating that ML-based functions are sufficiently safe to deploy and remain in operation as the environment and operational profiles evolve. This will include exploring so-called DevOps blending development and operations for ML and how the rapid heartbeat of DevOps (potentially hourly updates) can be aligned with the much slower dynamics of safety assurance processes. The main area of application covered by this role will be AI-enabled functions for Maritime Autonomous Surface Ships (MASS). For Grade 6, you must have a first degree in Computer Science or cognate discipline and a PhD in computer science, autonomous systems, or equivalent experience. Knowledge of Maritime Autonomy and associated systems, regulations, and standards sufficient to engage in high-quality research will be a significant advantage. You should have some experience in the application of machine learning technologies and ideally some knowledge of safety assurance and safety cases. Experience of carrying out both independent and collaborative research with the ability to write up research work for publication in high-profile journals and engage in public dissemination is required. For Grade 7, you must have a first degree in Computer Science or cognate discipline and a PhD in computer science, autonomous systems, or equivalent experience. Knowledge of Maritime Autonomy and associated systems, regulations, and standards sufficient to engage in high-quality research will be a significant advantage. You should have some experience in the application of machine learning technologies and ideally some knowledge of safety assurance and safety cases. Experience of carrying out both independent and collaborative research including supervision of the work of others and providing expert advice and guidance to external partners is necessary. 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 For informal enquiries: please contact Professor Simon Burton - simon.burton@york.ac.uk,