Centre for Doctoral Training in Machine Learning Systems PhD with Integrated Study 48 months PHD Programme By The University of Edinburgh |TopUniversities
Subject Ranking

# 24QS Subject Rankings

Programme Duration

48 monthsProgramme duration

Main Subject Area

Data Science and Artificial IntelligenceMain Subject Area

Programme overview

Main Subject

Data Science and Artificial Intelligence

Degree

PhD

Study Level

PHD

Study Mode

On Campus

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. 

Programme overview

Main Subject

Data Science and Artificial Intelligence

Degree

PhD

Study Level

PHD

Study Mode

On Campus

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. 

Admission Requirements

Entry requirements for individual programmes vary, so please check the details for the specific programme you wish to apply for on the University of Edinburgh website. You will also need to meet the University’s language requirements.

4 Years
Sep

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