[Fully-funded studentships covering fees and maintenance for eligible home students; limited funding for international students may be available.] The University of Cambridge is offering a fully-funded PhD studentship through the EPSRC Centre for Doctoral Training in Future Infrastructure and Built Environment: Unlocking Net Zero (FIBE3 CDT), in partnership with Ward & Burke, a leading engineering firm in water and wastewater infrastructure. This four-year (1+3 MRes/PhD) programme focuses on the development of advanced AI tools for meta-analysis of hydraulic models, aiming to prevent combined storm overflows and improve sewage network performance. The project addresses a critical gap in the global understanding and quantitative assessment of hydraulic models used for designing sewage network upgrades. Currently, model outputs are highly dependent on individual modellers, their assumptions, and model setups, leading to uncertainty in decision-making and scheme design. The research will develop computationally efficient meta-analysis techniques, leveraging AI and big data, to rank models, guide interventions, and assess the need for further optimisation. Key objectives include: developing a detailed understanding of current hydraulic modelling practices; creating a framework to quantitatively assess and rank catchment and sewage network models; providing guidance on sites and models that would benefit from further optimisation; and evaluating the cost, complexity, and embodied carbon of different intervention types. The project also explores blue/green and sustainable solutions to enhance network performance. Applicants should hold, or expect to obtain, at least a high 2.1 degree (preferably at Masters level) in any STEM subject, with strong quantitative and analytical skills. The studentship covers full fees and maintenance for eligible home students, with limited funding available for international candidates. For project-specific enquiries, contact Professor Dongfang Liang at [email protected]. General enquiries can be directed to [email protected]. Applications should be submitted online via the University of Cambridge Applicant Portal, clearly stating the project title and Professor Dongfang Liang as supervisor. Early applications are encouraged, as offers may be made before the deadline of 15 April 2026. Please note a £20 application fee applies. The University of Cambridge is committed to equality, diversity, and inclusion, welcoming applicants from all backgrounds. For further details on the programme, funding, and eligibility, visit the FIBE3 CDT website and the provided funding links. This opportunity is ideal for candidates interested in the intersection of civil engineering, environmental science, and AI-driven infrastructure optimisation.

[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.

[Fully-funded studentships covering fees and maintenance for eligible home students; limited funding for international students may be available later.] This fully-funded PhD studentship is offered through the Cambridge EPSRC Centre for Doctoral Training in Future Infrastructure and Built Environment: Unlocking Net Zero (FIBE3 CDT) at the University of Cambridge, in partnership with Ward & Burke, a leading engineering firm in water and wastewater infrastructure. The project aims to develop advanced AI tools for meta-analysis of hydraulic models, with the goal of preventing combined storm overflows and optimising sewage network upgrades. Current challenges in hydraulic modelling include a lack of global performance metrics and the dependence of model outputs on individual modellers' assumptions and setup. This project will address these issues by creating a new framework to quantitatively assess and rank catchment hydraulic models and sewage network models. Leveraging artificial intelligence and big data meta-analysis techniques, the research will enable computationally efficient evaluation of model quality, sensitivity to optimisation, and the cost and complexity of interventions. The project will also consider embodied carbon and the potential for blue/green and sustainable solutions to improve network performance. Key objectives include: developing a detailed understanding of current hydraulic modelling practices; designing a framework for quantitative assessment and ranking of models; providing guidance on which sites and models would benefit most from further optimisation; and evaluating the cost, complexity, and sustainability of different intervention strategies. The research will contribute to more informed decision-making in infrastructure design and environmental management, supporting the transition to net zero. Applicants should hold, or expect to obtain, at least a high 2.1 degree (preferably at Masters level) in a STEM subject, with strong quantitative and computational skills. Fully-funded studentships (covering fees and maintenance) are available for eligible home students, with limited funding for international students considered at a later stage. The University of Cambridge actively supports equality, diversity, and inclusion, and encourages applications from all backgrounds. Applications should be submitted online via the University of Cambridge Applicant Portal, clearly stating the project title and Professor Dongfang Liang as supervisor. Early applications are recommended, as offers may be made before the deadline of 15 April 2025. For project-specific enquiries, contact Professor Dongfang Liang at [email protected]. For general enquiries, email [email protected]. Further details about the programme and funding can be found at the provided links. Please note there is a £20 application fee.

[Fully-funded studentships covering fees and maintenance for eligible home students; limited funding for international students may be available later.] The University of Cambridge is offering 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 is designed for candidates passionate about advancing building decarbonisation using data-intensive, AI-driven thermodynamic models. The project is delivered in collaboration with CamDragon Co. Ltd, a Cambridge-based SME specialising in engineering consultancy, flood-risk evaluation, geohazard assessment, and sustainable drainage solutions across the UK, China, and Australia. Research will focus on developing predictive AI tools for spatiotemporal heat transfer in buildings, aiming to optimise thermodynamics and occupant comfort. Machine learning algorithms will be employed to identify energy inefficiencies and propose adaptive strategies, while theoretical and empirical approaches will enhance wellbeing and reduce carbon emissions. Key objectives include constructing advanced AI algorithms for forecasting heat flow and comfort metrics, identifying drivers of energy inefficiency, formulating AI-driven control strategies, assessing heat pump readiness, and producing guidelines for scalable, data-rich design and operation frameworks in diverse building contexts. Applicants should hold, or expect to obtain, a high 2.1 degree (preferably at Masters level) in Civil Engineering. Essential skills include data analytics, programming (Python, MATLAB), strong communication, and the ability to integrate numerical modelling, sensor technologies, and occupant-focused design. Experience in thermodynamics, building physics, or machine learning is desirable, and familiarity with energy systems or HVAC design is advantageous. Funding covers full tuition fees and maintenance for eligible home students, with limited opportunities for international students considered later in the recruitment process. For further details on eligibility and funding, refer to the provided UKRI and Cambridge Trust links. The University of Cambridge actively supports equality, diversity, and inclusion, encouraging applications from all backgrounds. To apply, visit the University of Cambridge application portal, select the relevant course code (EGEGR3), and specify the project title. A £20 application fee applies. Early applications are recommended as offers may be made before the stated deadline of 2 March 2026. For project-specific enquiries, contact Prof. Dongfang Liang at [email protected].