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EPSRC CDT Machine Learning Systems -Funded PhD Programme

Job in Edinburgh, City of Edinburgh Area, EH91, Scotland, UK
Listing for: WiMLDS Inc
Full Time position
Listed on 2025-10-23
Job specializations:
  • Education / Teaching
    Data Scientist
Job Description & How to Apply Below
Position: EPSRC CDT Machine Learning Systems Fully-Funded PhD Programme
Location: City of Edinburgh

This CDT develops researchers with expertise across the systems-ML stack. 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.

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.

The CDT has a minimum of 10 fully-funded studentships available for September 2026 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 (about 3 per year).

Ideal Candidate
  • 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.

We are particularly interested in receiving applications from Female and Home applicant.

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