Research Fellow (107880-0924)

Location: University of Warwick Campus, Coventry

Duration: Ending 31 May 2027

About the Role

For informal enquiries, please contact Siddartha Khastgir (Professor (Research Focussed)) at Siddartha.khastgir.1@warwick.ac.uk. 

We are looking for a talented AI engineer to join our team developing safe and reliable AI systems for Connected and Autonomous Vehicles (CAVs). In this role. You will develop and apply advanced techniques in machine learning (ML) testing, formal verification, uncertainty quantification, ML safety monitors and explainable AI (XAI) to ensure CAV meet the highest safety standards.

About You  

You will undertake research in order to support the work of the department and develop and enhance its reputation, both internally and externally. Assist the Project Leader and, where appropriate, project collaborators in the successful execution of the project. You will conceptualise, architect, implement and successfully lead applied research and engineering activities in the area of Safe AI for CAV. You will enhance the impact of the research and engineering activities via publications, networking, PR-communications, standardisation/regulatory work, and broad stakeholder engagement. You will be a team player, willing to constrictively receive and provide critical assessments of work. You will act as leader internally and externally in your area of domain expertise.

You are expected to conduct (some of) the following research in Safe AI:

• To design and implement novel testing frameworks (e.g., coverage-guided, distribution-aware, metamorphic, statistical and operational) to thoroughly evaluate the robustness, fairness, security, etc. of ML models for Connected and Autonomous Vehicles (CAV) perception, control, and planning tasks.
• To apply formal verification methods (e.g., formal reachability analysis) to prove safety properties and the absence of dangerous behaviours in ML models.
• To quantify uncertainties (by, e.g., conformal prediction, ensembles, bootstrapping, and evidential deep learning) in ML model outputs and incorporate them into system-level decision-making.
• To develop and deploy reliable runtime ML safety monitors (e.g., Out-Of-Distribution detectors) that can detect anomalies and enable safe fallbacks.
• To devise and apply novel Explainable AI (XAI) methods, in the application context of CAVs, to explain ML model behaviours and decisions to stakeholders.
• To fine-tune Generative AI models with safe AI considerations, for CAV applications

For further information regarding the skills required for this role please see the personal specification section of the attached job description.

If you are near submission or have recently submitted your PhD but have not yet had it conferred, any offers of employment will be made as Research Assistant at the top of level 5 of the University grade structure. Upon receipt of evidence of the successful award of your PhD, you will be promoted to Research Fellow on the first point of level 6 of the University grade structure. 

CLOSING DATE: Monday 16 September 2024 at 11.55 pm

Full details of the duties and selection criteria for this role can be found in the vacancy advert on the University of Warwick's jobs pages. You will be routed to this when you click on the Apply button.

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