PhD Studentship (Ref 5598) - AI-Enhanced Digital Twin for Sustainable Manufacturing (Engineering Department Funded)
About the award
Supervisors
Dr Natalia Hartono - University of Exeter - Faculty of Environment, Science and Economy
Dr Martino Luis - University of Exeter - Faculty of Environment, Science and Economy
Manufacturing industries face mounting pressure to reduce environmental impact whilst maintaining efficiency and competitiveness. Traditional approaches often lack real-time insights and predictive capabilities needed for truly sustainable operations.
Research Question: How can AI-enhanced digital twin technologies with advanced optimisation algorithms transform manufacturing processes to achieve sustainability goals whilst improving operational efficiency?
This PhD studentship will involve developing machine learning models, creating virtual manufacturing replicas, and implementing optimisation algorithms. Daily activities include coding, data analysis, simulation modelling, and collaboration with industry partners. Some travel to manufacturing facilities and conferences may be required.
This funded PhD scholarship is suitable for students with a background in Engineering, Mathematics, and Computer Science. Students with interests in machine learning, deep learning, AI, intelligent decision making, are encouraged to apply. Programming experience and analytical skills are highly valued.
The studentship will be awarded on the basis of merit. Students who pay international tuition fees are eligible to apply, but should note that the award will only provide payment for part of the international tuition fee and no stipend.
International applicants need to be aware that they will have to cover the cost of their student visa, healthcare surcharge and other costs of moving to the UK to do a PhD.
The conditions for eligibility of home fees status are complex and you will need to seek advice if you have moved to or from the UK (or Republic of Ireland) within the past 3 years or have applied for settled status under the EU Settlement Scheme.
Entry requirements
Applicants for this studentship must have obtained, or be about to obtain, a First or Upper Second Class UK Honours degree, or the equivalent qualifications gained outside the UK, in an appropriate area of engineering, mathematics, and computer science.
If English is not your first language you will need to meet the English language requirements and provide proof of proficiency. Click here for more information.