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EPSRC CDT in Machine Learning Systems

EPSRC CDT 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.

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.

Find out more

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.

Why Edinburgh?

The School of Informatics (SoI) has one of the largest concentrations of research in Europe in machine learning and computer systems, with over 80 world-leading supervisors. In the REF 2021, the SoI ranked first for research power and scored 100% both for Research Environment and Impact. The Times Higher Education placed UoE in fifth place globally for innovation, industry and infrastructure in both 2022 and 2023.

How to apply/deadlines: TDC

Contact: a.storkey@ed.ac.uk