Machine Learning (ML) has a great impact on our daily lives. Developments in ML are built on improved systems that can train and generate increasingly powerful models. Systems design greatly impacts ML performance and capability.

Major advancements are made when ML and systems are developed and optimised together. This is relevant across many industries such as:

• in-car systems
• medical devices
• mobile phones
• sensor networks
• condition monitoring systems
• high-performance computing
• the creative industries
• patient care
• social networking
• high-frequency trading

However, PhD training that combines systems and ML is rare, as research training is often separated into individual subdisciplines.

Instead, we need researchers trained in both fields and experienced in working across them. This ML Systems PhD involves training collaborative researchers with experience across systems and ML.

The programme is about machine learning that works to deliver for a need. It involves a holistic view of machine learning and systems that includes both a user-centric approach and an understanding of how to make things work.