CDT Machine Learning Systems PhD

About the CDT

Centre for Doctoral Training in Machine Learning Systems

Machine Learning has a dramatic impact on our daily lives built on the back of improved computer systems. Systems research and ML research are symbiotic. Modern systems research targets the ubiquitous need for efficient ML. ML research, conversely, is directly affected by how methods will be deployed. Furthermore, systems research increasingly explores ML methods to improve systems, and ML research develops such methods.

Major gains are made when the development of ML and systems are symbiotic and co-optimized. This is relevant across a broad spectrum of industries: in-car systems, medical devices, phones, sensor networks, condition monitoring systems, high-performance compute, and high-frequency trading.

This CDT will develop researchers with expertise across the systems-ML stack. Company engagement is an integral part of the programme with built-in internships alongside entrepreneurship training. The PhD programme in Machine Learning Systems will position students for strong, ethically aware technical careers, developing the next generation of leaders. . This makes a cohort-based programme vital, treating ML Systems as a holistic discipline. Cohort interaction, and integration, give students real experience across multiple systems, approaches and methodologies. Company engagement is an integral part of the programme with built-in internships alongside entrepreneurship training.

Students must have a broad understanding of different hardware designs, different platforms, different environments, different models, and different goals beyond their immediate research focus. Individual supervisory teams rarely have this breadth of knowledge. This makes a cohort-based CDT vital, treating ML Systems as a holistic discipline. Cohort interaction, and integration gives students real experience across multiple systems, approaches and methodologies.

The PhD programme in Machine Learning Systems positions students for strong, ethically aware technical careers, developing the next generation of leaders. Students will develop foundational research skills in Computer Systems, Machine Learning, Hardware, Sensors and Control, Programming and Integrated Machine Learning Environments, AI Ethics, and Leadership and Entrepreneurship. At the end, all students will have extensive experience of real-world deployment and optimization of machine learning methods.

Candidate’s profile

An ideal candidate would typically have:

• a strong degree or higher qualification in a relevant field (e.g. computer science, mathematics, engineering, physical sciences, economics or any other field where evidence is provided of sufficient computing and mathematical background)
• solid experience of programming, machine learning methods and ideally deep learning environments (e.g. pytorch) or a computer systems background

Our vision

Students will develop foundational research skills in Computer Systems, Machine Learning, Hardware, Sensors and Control, Programming and Integrated Machine Learning Environments, AI Ethics, and Leadership and Entrepreneurship.

At the end, all students will have extensive experience of real-world deployment and optimization of machine learning methods. A critical facet of both systems and machine learning research is integration; supported by a research engineer, the CDT will create a consistent repository for research results – data, software, tools – usable across the cohort and beyond, and provide a pathway tooling for entrepreneurship and spinout companies. Companies are involved at many levels within the CDT; internships are explicitly built into the programme and entrepreneurship training is at the fore.

CDT studentships

• The CDT has a minimum of 10 fully-funded studentships available for September 2025 entry.
• Studentships include stipend, fees and research costs for 4 years.
• As a UKRI-funded CDT, application is open to all UK/EU/non-EU citizens providing they meet the university PhD entry requirements.
• However, the number of students with international fees status that can be recruited is restricted.

An indication of the fees status categories, entry requirements and further details on eligibility criteria can be found on our website.

Why Edinburgh?

The University of Edinburgh is one of the best research-intense Universities in the world.

The School of Informatics that hosts the CDT is consistently ranked among the world’s top 30 computer science departments. In 2024 QS World University Ranking by Subject, it is ranked 20^th for Computer Science and Information System, and 21^st for Data Science and AI.

Edinburgh graduates are ranked 24th in the world by employers according to QS World University Rankings 2025.

Ranked 13th in the world’s top student cities in the QS Student Cities ranking (2025), Edinburgh is a modern, sophisticated and beautiful European city with a diverse, multicultural community.

The CDT students will be hosted in the state-of-the-art Informatics Forum in the heart of Scotland’s capital, consistently considered one of the most desirable places to live in the world.

How to apply

The deadline for applications is 22nd January 2025.

Contact mlsystems-enquiries@inf.ed.ac.uk

ML Systems Website