KTP Research Associate: AI for innovative and sustainable retrofit design

This is an exciting opportunity for someone with a postgraduate/doctoral degree in Building Physics, Building Performance Modelling, Data Analytics for Smart Buildings, Machine Learning or a closely related subject. The post holder will lead a cutting-edge innovation project that will implement Artificial Intelligence in ECD Architects to improve productivity within the practice and develop a new service that can improve the design process of housing projects.

Based at ECD London office, the KTP Associate will coordinate the development of this innovative project from the beginning to the end and engage with industry stakeholders to establish himself/herself as a thought leader in the field of implementing AI in the construction sector. This will involve a review of the existing workstreams and data management practices, implementing AI and machine learning principles to automate data processing and enhance the efficiency and quality of data processing for retrofit projects within ECD, and develop an AI model for building performance prediction at the early stages of design. Plus, the successful candidate will be part of the prestigious 48-year-old national Knowledge Transfer Partnership programme offering a dedicated professional development budget, a network of fellow Associates from many disciplines and training and mentoring opportunities. The Associate will also have the opportunity to write publications about their work alongside the academic and company team.

The vacancy is available from 01 January 2025 and the successful candidate must be in post by 01 February 2025. The post has funding for 12 months in the first instance, further funding to support the post may be available. If you have any queries regarding the vacancy, or the application process, please contact bseer-recruitment@ucl.ac.uk. If you have specific questions about the role please contact Dr Esfand Burman, esfand.burman@ucl.ac.uk

The KTP Associate is responsible for the day-to-day running of the project. The Associate will be expected to show initiative and independence of thought in applied research and embedding knowledge. They will also demonstrate inquisitive and project management skills in their industry-based role. Specifically, this includes:

1. Develop an in-depth understanding of the ECD workstreams and data management practices and identify improvement opportunities.
2. Implement AI and machine learning principles to automate data processing, reduce repetitive tasks, and enhance the efficiency and quality of data processing for retrofit projects within ECD.
3. Identify the current ECD workstreams that are resource intensive in retrofit projects for evaluation of energy and sustainability (e.g., SAP or Passivhaus tools) and develop an AI-based model for retrofit projects as a new offering at the early design stages.
4. Evaluate the project’s deliverables at the initial Phase of implementation at ECD.
5. Disseminate the key outputs of the project and ensure longer term benefits for the Business Partner (ECD) and the Knowledge Base (UCL) beyond the duration of the KTP.