The overarching aim of the KTP is to address a key barrier to the adoption of artificial intelligence in safety-critical energy applications: the lack of trusted, structured and regulator-ready safety cases for non-deterministic AI systems. The key responsibilities of the project and KTP associate are:

Review the cutting-edge AI technologies currently being developed and/or deployed within the energy sector
Engage actively with various teams within DNV to gain an understanding of DNV's current practices, and the impact AI technologies will bring to existing processes
Lead on the development of existing methodologies for the safe life-cycle of AI components, such as AMLAS, and the refinement required for the energy sector
Apply the acquired knowledge, and newly developed techniques for assuring AI technologies on a real-world application of a safety critical energy system.

The post holder should have demonstrable experience of conducting research; this can be in the form of a PhD (or close to completion), a Masters degree, or equivalent industrial experience.
Have an understanding of AI technologies or systems safety
Excellent communication skills, both written and oral, for disseminating research outcomes to all parties involved in the KTP
Can conduct work both independently and collaboratively, especially in a multidisciplinary environment
Be committed to the values of equality, diversity and inclusion

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

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