Management and Business: Fully Funded PhD in Management and Business: Machine Learning for Energy Poverty Prediction (RS816)

Funding provider: ESRC WGSSS 50% Swansea University 50% 

Subject areas: ESRC WGSSS studentship- Management and Business pathway 

Project start date: 1st October 2025 (enrolment open from mid-September)

Supervisors: Lead Supervisor: Dr Hamidreza Eskandari, Co-supervisor: Dr Daniele Doneddu

Aligned programme of study: PhD in Business Management  

Mode of study: Full or Part-time study is possible. Please note that full-time ESRC WGSSS studentship award holders cannot hold either a full-time job, permanent part-time job or temporary role for an extended period of time, during the period of their award. Part-time ESRC WGSSS studentship award holders cannot hold a full-time job. 

Place of Study: Swansea University 

Project Description: 

Energy poverty (EP) is a pressing socio-economic challenge in the UK, disproportionately affecting households with limited financial resources and poor-quality, energy-inefficient housing. Recent figures indicate that approximately 6.7 million households were classified as fuel poor in 2023, underscoring the urgency of the issue. The consequences of EP extend far beyond financial hardship, contributing to serious health risks, reduced well-being, and increased strain on public services. 

This project directly addresses the need for more effective, data-driven EP interventions by developing advanced, explainable machine learning (ML) models that continuously learn from a rich array of historical and socio-economic data. These include household income, energy expenditures, dwelling characteristics, and property conditions. The primary objective is to accurately predict households at risk of energy poverty, enabling timely and targeted responses from policymakers, energy suppliers, and social services. Early identification can help mitigate long-term social, economic, and health impacts—ultimately improving quality of life and reducing inequality. 

The Welsh Government (WG) has demonstrated strong support for research in this area, recognising its alignment with their Programme for Government and wider commitments to social justice, climate resilience, and energy equity. This project aims to go beyond academic inquiry by providing evidence-based, actionable tools to support decision-making at multiple levels of governance. 

A key innovation of this project lies in its emphasis on explainable AI, ensuring that predictions are transparent, interpretable, and accountable—critical factors for building trust among stakeholders and ensuring practical adoption. In doing so, the project advances both local and global policy objectives, including several of the UN Sustainable Development Goals (SDGs). 

By introducing a novel ML-based predictive framework tailored specifically to the dynamics of energy poverty, this project will contribute a scalable, adaptable solution that supports the design of targeted, equitable, and sustainable interventions. 

Research Objectives: 

✅ Enhance the understanding of EP in Wales through ML-driven data analysis. 

✅ Develop advanced feature selection methods to identify key drivers of EP. 

✅ Create an ML-based classification framework to categorize households by EP risk levels. 

✅ Implement predictive ML models to identify households at risk of EP early. 

✅ Design adaptable solutions that support the targeted and sustainable interventions. 

The duration of study varies from 3.5 to 4.5 years full time (or part time equivalent).      

The duration study is dependent on prior research experience and training needs of the student which will be assessed by completing a Development Needs Analysis.  

Student profile (but not limited to):  

AI & Machine Learning, Social Sciences, Industrial Engineering, Statistics, Computer Science, Data Analytics, etc. 

We welcome applications for both full and part-time study.    

Research in practice placement:    
All WGSSS funded students are required to complete a funded Research in Practice placement of 3-months in total (or part-time equivalent). All students will have the opportunity to complete a placement in academia, policy, business or civil society organisations. 

To receive WGSSS studentship funding, you must have qualifications or experience equivalent to an UK honours degree at a first or upper second-class level, or a master's from a UK academic research organisation.  See – Country Specific Information for International Applicants 2025  

WGSSS studentships are available to home and international students. Up to 30% of our cohort can comprise international students. International students will not be charged the fee difference between the UK and international rate. Applicants should satisfy the UKRI eligibility requirements.   

The WGSSS is committed to supporting and promoting equality and diversity and to creating an inclusive environment for all. We welcome applications from all members of the global community irrespective of age, disability, sex, gender identity, gender reassignment, marital or civil partnership status, pregnancy or maternity, race, religion or belief and sexual orientation. 

English Language: IELTS 6.5 overall (with no individual component below 6.5) or Swansea University recognised equivalent.  Full details of our English Language policy, including certificate time validity, can be found here.

This studentship funded by ESRC WGSSS covers the full cost of tuition fees in line with UKRI minimum rate currently £19,237 for 2024/2025 with an uplift to £20,780 in 2025/2026.

Students also have access to a Research Training Support Grant of £940 per year in 2025/2026. 

If you have a disability, you may be entitled to a Disabled Students’ Allowance (DSA) on top of your studentship.

To apply, please complete your application online here via the APPLY System with the following information:

1. Course choice – please select as per preferred mode of study, either: 

(Full Time) Business Management / PhD / Full-time / 3 Years / October 

OR 

(Part Time) Business Management / PhD / Part-time / 6 Years / October 

In the event you have already applied for the above programme previously, the application system may issue a warning notice and prevent application, in this event, please email pgrscholarships@swansea.ac.uk where staff will be happy to assist you in submitting your application. 

1. Start year – please select 2025 

1. Funding (page 8 on the application process) – 

• ‘Are you funding your studies yourself?’ – please select No 

• ‘Name of Individual or organisation providing funds for study’ – please enter  ‘RS816 - WGSSS Business’ 

*It is the responsibility of the applicant to list the above information accurately when applying, please note that applications received without the above information listed will not be considered for the scholarship award. 

One application is required per individual Swansea University led research scholarship award; applications cannot be considered listing multiple Swansea University led research scholarship awards. 

Please include the following documents with your application:    

• WGSSS Application Form – this FULLY COMPLETE form MUST be added as an attachment into your Swansea University application account.   

• Academic CV (two pages maximum)  

• 2 academic or professional references (candidates must approach referees themselves and include references with their application. The reference must detail the applicant’s research strengths).  

• Degree certificates and Transcripts (including translations if applicable)    

• If relevant, proof of English Language Competency (see institutional requirements for entry)   

Assessment:  Short-listed applicants will be invited to interview. As part of the interview process, applicants will be asked to give a short presentation and answer a series of panel questions  

NOTE: Applicants for PhD/EngD/ProfD/EdD - to support our commitment to providing an environment free of discrimination and celebrating diversity at Swansea University you are required to complete an Equality, Diversity and Inclusion (EDI) Monitoring Form in addition to your programme application form.    

Please note that completion of the EDI Monitoring Form is mandatory; your application may not progress if this information is not submitted. 

Supervisory Team: Lead Supervisor: Dr Hamidreza Eskandari Co-supervisor: Dr Daniele Doneddu  

Informal enquiries are welcome; please contact Dr Hamid Eskandari hamidreza.eskandari@swansea.ac.uk 

*External Partner Application Data Sharing – Please note that as part of the scholarship application selection process, application data sharing may occur with external partners outside of the University, when joint/co- funding of a scholarship project is applicable.