EPSRC FIBE3 CDT PhD Studentship: Data-Intensive AI Thermodynamic Models for Next-Generation Building Decarbonisation University of Cambridge in United Kingdom

[Fully-funded studentships covering fees and maintenance for eligible home students; limited funding for international students may be available at a later stage.]

The University of Cambridge invites applications for a fully-funded PhD studentship through the EPSRC Centre for Doctoral Training in Future Infrastructure and Built Environment: Unlocking Net Zero (FIBE3 CDT). This four-year (1+3 MRes/PhD) programme, in collaboration with CamDragon Co. Ltd, focuses on developing data-intensive, AI-driven frameworks to optimise thermodynamics and occupant comfort in the built environment. The project aims to create predictive AI tools for spatiotemporal heat transfer, using machine learning algorithms to identify energy inefficiencies and propose adaptive strategies for carbon reduction and enhanced wellbeing.

Key objectives include constructing advanced AI algorithms for forecasting and visualising heat flow and comfort metrics, identifying drivers of energy inefficiency such as occupant behaviour and heat loss hotspots, and formulating AI-driven control strategies for comfort and carbon optimisation. The research will also assess heat pump readiness and propose interventions for low-carbon retrofits, ultimately producing guidelines for scalable, data-rich design and operation frameworks applicable to diverse building contexts.

The studentship is fully funded for eligible home students, covering both tuition fees and maintenance. A limited number of international students may be considered for funding at a later stage. Applicants should hold, or expect to obtain, a high 2.1 degree (preferably at Masters level) in Civil Engineering, with strong skills in data analytics, programming (Python, MATLAB), and excellent communication. Experience in thermodynamics, building physics, or machine learning is desirable, and familiarity with energy systems or HVAC design is advantageous.

To apply, candidates should submit an online application via the University of Cambridge postgraduate portal, quoting course code EGEGR3 and specifying the project title and supervisor (Prof. Dongfang Liang). Early applications are encouraged as offers may be made before the deadline of 2 March 2025. For project-specific enquiries, contact Prof. Dongfang Liang at [email protected]. The University of Cambridge is committed to equality, diversity, and inclusion, and welcomes applications from all backgrounds.