AI-Driven Optimisation for Energy-Efficient Smart Buildings

Summary

Project Summary

Artificial Intelligence is revolutionising how we approach climate challenges in the built environment. This fully funded PhD opportunity will equip you to develop a hybrid AI system that optimises the performance of smart building technologies — specifically HVAC and refrigeration systems — improving energy efficiency without compromising comfort, reliability, or safety.

In collaboration with LoweConex, a leading software and analytics provider for connected building assets, this project combines machine learning, physics-based models, and expert domain knowledge to deliver real-time optimisation that is explainable, scalable, and impactful.

With access to one of the UK's largest IoT energy datasets, this is a unique opportunity to contribute to the development of AI systems that directly support organisations in achieving Net Zero carbon goals.

Research Objectives

• Identify the key drivers influencing the operation and energy consumption of connected building assets.
• Develop a decision-making framework that integrates:
  • Advanced machine learning methods (e.g. reinforcement learning),
  • Physics-based models of system behaviour,
  • Expert and regulatory knowledge,
  • Multi-modal datasets including telemetry, weather, maintenance logs, and potentially video.
• Enable real-time optimisation of energy use, even with delayed data (e.g. day+1 MPAN data).

Industrial Partnership with LoweConex

You will work closely with LoweConex, gaining access to:

• Telemetry from over 165,000 connected assets
• More than 2 billion data points collected daily across sectors (retail, commercial property, manufacturing)
• A modern, scalable data platform for experimentation and deployment
• Real-world validation and co-production of tools

Engagement includes:

• Three formal secondments (induction, mid-project co-design, final phase deployment)
• Monthly site visits and mentoring from LoweConex engineers and data scientists
• Participation in industry-led workshops and dissemination events

Training and Supervision

Hosted at Ulster University, you will join a multi-disciplinary research team with expertise in:

• Artificial intelligence and explainable ML
• Smart energy systems and building performance
• Asset management and digital infrastructure

You will receive tailored training in:

• Machine learning frameworks (e.g. TensorFlow, PyTorch)
• Hybrid modelling and optimisation
• Data science for IoT environments
• Research translation and industry collaboration

Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study, such as:

• Computer Science, Artificial Intelligence or Data Science
• Mechanical/Electrical Engineering
• Energy Systems or Built Environment
• Applied Physics or Mathematics

Applicants should also have

• A passion for applying AI to real-world, sustainability-focused problems
• Excellent problem-solving and communication skills

Essential criteria

Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.

We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.

In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.

• Experience using research methods or other approaches relevant to the subject domain

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

• First Class Honours (1st) Degree
• Masters at 70%
• Experience using research methods or other approaches relevant to the subject domain
• Work experience relevant to the proposed project
• Publications - peer-reviewed
• Experience of presentation of research findings

Equal Opportunities

The University is an equal opportunities employer and welcomes applicants from all sections of the community, particularly from those with disabilities.

Appointment will be made on merit.

Funding and eligibility

This project is funded by:

• DfE CDP Award in collaboration with LoweConex

The University offers the following levels of support:

Department for the Economy (DFE) Scholarship

These scholarships will cover tuition fees and provide a maintenance allowance of £19,237 (tbc) per annum for three years (subject to satisfactory academic performance). A Research Training Support Grant (RTSG) of £900 per annum is also available.

• Candidates with pre-settled or settled status under the EU Settlement Scheme, who also satisfy a three-year residency requirement in the UK prior to the start of the course for which a Studentship is held MAY receive a Studentship covering fees and maintenance.
• Republic of Ireland (ROI) nationals who satisfy three years’ residency in the UK prior to the start of the course MAY receive a Studentship covering fees and maintenance (ROI nationals don’t need to have pre-settled or settled status under the EU Settlement Scheme to qualify).
• Other non-ROI EU applicants are considered ‘International’ and are not eligible for this source of funding.
• Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Due consideration should be given to financing your studies. Further information on cost of living

This CDP studentship covers three years of tuition fees (worth over £14,000) and offers an annual non-taxable maintenance grant of approx. £19,500 plus an additional industrial stipend top-up of £6000 per annum from LoweConex (that is, total tax-free stipend: approx. £26,000 annually, equivalent to ~£30K gross salary), with additional budget of £40,500 over 3 years for 1) travel and subsistence for secondments; 2) research training, project running cost, equipment and conference attendance.

To be eligible for these scholarships, applicants must meet the following criteria:

• Be a UK National, or

• Have settled status, or

• Have pre-settled status, or

• Have indefinite leave to remain or enter, or

• be an Irish National

Applicants should also meet the residency criteria which requires that they have lived in the EEA, Switzerland, the UK or Gibraltar for at least the three years preceding the start date of the research degree programme.

Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Due consideration should be given to financing your studies.