PhD Opportunities

PhD supervision at DIAL is given by Prof. Duncan McFarlane. Please inquire directly.

Funding may be available at EPSRC levels for UK / EU students. For overseas students, funding might be available through the Cambridge International Scholarship Scheme. Potential applicants are also encouraged to visit the Cambridge Trust website and the university's website on graduate funding for more information regarding funding opportunities. 

Specific PhD opportunities are given below.

PhD in Industrial Automation Systems

A PhD project is available investigating the development of tools and methods for determining the value of industrial automation systems. The PhD position will conduct a review of tools and methods in economics and engineering for assessing automation & information systems; perform a  series of industrial case studies focussed on a class (or classes) of automation developments; develop a framework for assessing holistic automation value and impact; and perform mathematical analysis to demonstrate differential impact of a type of automation. 

PhD in Low-Cost Digital Solutions for Industrial Sustainability 

A PhD project is available exploring the design and deployment of low-cost digital solutions for industrial sustainability. The PhD position will aim to identify the class of (low-cost) digital solutions that impact on industrial sustainability; assess industry sustainability standards linked to selected focus sectors; and determine a method for aligning sustainability targets with sets of digital solutions.

Phd in Reference Architecture Driven Design of Industrial Automation Systems

A PhD project is available to investigate reference architecture driven design of industrial automation systems. The PhD position will aim to provide a user-driven classification of reference architectures (RAs) relevant to automation system design and identify gaps.

PhD in Executable Digital Twins for Edge Computing 

A PhD project is available to investigate Executable Digital Twins for edge computing using non-intrusive smart sensoring approaches and advanced data analytics. The PhD position will propose approaches and solutions to create Executable Digital Twins (xDTs) suitable for edge-computing applications for retrofitting activities; and develop concrete solutions of non-intrusive, robust, light and portable modelling and analytical techniques. 

For questions please contact Professor Duncan McFarlane, dm114@cam.ac.uk.