AI and Interoperable Methods to Support Energy Modeling of the Future Building Stock University of Limerick in Ireland

The University of Limerick is offering a fully funded PhD position focused on developing AI and interoperable methods to support energy modeling of the future building stock. This research is part of a national-scale initiative to create a digital twin of Ireland’s built environment, enabling data-driven decision-making in energy efficiency, climate resilience, urban planning, and policy making. The project aims to model energy renovation strategies across multiple geographical scales, from individual buildings to districts and the national level, using advanced energy modeling techniques such as white box, grey box, and black box solutions.

The successful candidate will contribute to the semantic infrastructure underpinning this digital twin, with a focus on integrating, interoperating, and intelligently querying building-related data to support large-scale building renovation. The research will involve developing and applying semantic web technologies, including ontologies, linked data, and knowledge graphs, to represent and reason about building information at scale. The use of novel AI agents for interacting with these graphs is also a key component. The work will be grounded in real-world datasets and national initiatives, contributing to the design of scalable, standards-compliant semantic models for Ireland’s building stock.

This PhD project is closely linked to the NexSys project and the Building Energy Informatics Group at University College Dublin, with Prof James O'Donnell serving as the supervisor. The candidate will have opportunities to collaborate with interdisciplinary teams, engage with stakeholders, and participate in academic and industry internships. The position offers advanced research training, critical problem-solving experience, and a strong foundation for a career in energy technologies, environmental engineering, and information systems.

Applicants should possess a high honours Bachelor’s or Master’s degree (2.1 or higher) in Computer Science, Engineering, or a related discipline, or have equivalent industry experience. Required skills include strong programming abilities (Python, JavaScript, SPARQL), familiarity with semantic technologies (RDF, OWL, SHACL) or large databases, and excellent English communication skills. Desirable skills include experience with building data formats (IFC, gbXML, CityGML), machine learning, building physics, thermodynamics, and energy modeling tools (EnergyPlus, IES VE, TRNSYS, Modelica). Candidates should demonstrate research experience, attention to detail, organizational skills, and the ability to manage complex workloads and deadlines.

The scholarship covers a stipend of €25,000 per annum, travel/consumables/materials budget, and tuition fees for up to four years. The application process requires submission of a cover letter and CV via email to Prof James O'Donnell at [email protected] by February 1, 2026. This is an excellent opportunity for motivated students to contribute to cutting-edge research at the intersection of energy modeling, AI, and digital infrastructure for sustainable built environments.