Supervisory Team: Dr. Massimiliano Manfren and Prof. Patrick AB James
Applications are invited for a fully-funded PhD studentship working on data-driven interpretable building energy analytics. The PhD student will join a world-leading research team based within the Sustainable Energy Research Group (SERG) at the University of Southampton, a member of the Russell Group and ranked in the world’s top 100 Universities. The PhD studentship is funded by the University of Southampton. The successful applicant will join the SERG team within the Energy & Climate Change Division (ECCD).
The research work in this project will be a combination of theoretical and experimental activities centred on data-driven building energy modelling. Over the last two decades, machine learning has been developed and tested in building research, aided by increased data availability, powerful and affordable computing resources, and advanced algorithms, and has demonstrated its potential to improve building performance. The methods used will address both operational and embodied energy and carbon in new construction and retrofit.
The primary goal of this PhD project will be to create an interpretable “digital twin” approach for data-driven energy modelling. A “digital twin” is a digital replica of a physical object, process, or service that can overcome the limitations of traditional simulation-based engineering approaches.
While simulations and digital twins are both virtual representations of objects, digital twins can verify how a physical object, process or service performs in real time and in real world conditions. Furthermore, interpretable data-driven methods can be designed to combine human and machine intelligence in a “human-in-the-loop approach” whose fundamental goal is to accelerate the transition to Net Zero of the building stock.
The other primary goal will be to develop the “digital twin” approach so that it can be applied at various stages of the building life cycle, from early design to operation, and that it is scalable, from whole-building analysis downwards to individual building technologies and upward to clusters of buildings.
A very good undergraduate degree (at least a UK 2:1 honours degree, or its international equivalent).
Closing date: applications should be received no later than 31 August 2022 for standard admissions, but later applications may be considered depending on the funds remaining in place.
Fully funded for UK students, Tuition Fees and a stipend of £15,609 tax-free per annum for up to 3.5 years.
How To Apply
Applications should be made online. Select programme type (Research), 2022/23, Faculty of Physical Sciences and Engineering, next page select “PhD Engineering & Environment (Full time)”. In Section 2 of the application form you should insert the name of the supervisor Massimiliano Manfren
Applications should include:
Two reference letters
Degree Transcripts to date
For further information please contact: email@example.com
The School of Engineering is committed to promoting equality, diversity inclusivity as demonstrated by our Athena SWAN award. We welcome all applicants regardless of their gender, ethnicity, disability, sexual orientation or age, and will give full consideration to applicants seeking flexible working patterns and those who have taken a career break. The University has a generous maternity policy, onsite childcare facilities, and offers a range of benefits to help ensure employees’ well-being and work-life balance. The University of Southampton is committed to sustainability and has been awarded the Platinum EcoAward