Research Assistant or Associate

As a Research Assistant or Associate in Scheduling, the work centres on this position will carry out research into Physics-Informed Graph Neural Networks (PIGNN) for digital manufacturing. It would suit someone who can bring careful technical judgement and practical problem-solving to the role.

Known job details

• Location: Scheduling
• Pay: £43,863 - £47,223
• Additional detail: Training or development support may be provided.

Likely focus of the role

• This position will carry out research into Physics-Informed Graph Neural Networks (PIGNN) for digital manufacturing.
• Processing dynamics and are composed into workflow-level models that integrate scheduling and congestion effects.

Requirements mentioned

• Proven research in AI for systems modelling, or physics-informed and graph-based machine learning, or digital manufacturing, with Demonstrations of the ability to build proofs-of-c.
• Masters degree (or equivalent) in Computer Science or a closely related discipline.
• Experience in publishing research in leading conferences and journals.