Applied Symbolic AI

Description

We have an exciting opportunity to offer for a PhD student with an interest in foundational AI techniques. You can enjoy developing and applying them in a setting that will push forward the boundaries of science discovery. Your PhD will firmly sit within Computer Science, while being part of a wider interdisciplinary team on an EPSRC Programme Grant on the topic of “Navigation of Chemical Space for Function”. You will contribute to the development of a digital discovery platform that blends machine learning and explainable symbolic AI reasoning methods from computer science with physical science (PS) synthesis, measurement and computation capability and work closely with chemists to capture the domain expertise in the CS models being developed and applied.

We seek a candidate familiar with (or interested in) foundational AI techniques, such as satisfiability and constraint solving, optimisation, or explainable AI. Ideal candidates will have knowledge or interest in one of these areas and a willingness to embrace interdisciplinary research.

The starting date is flexible.

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