Smart Indoor Air Quality Systems for Healthier Living

Apply and key information  

This project is funded by:

    • Department for the Economy (DfE)

Summary

Air pollution is often seen as an outdoor issue, yet we spend 80-90% of our time indoors, where surprisingly, air quality can be of lower quality - contributing to respiratory diseases, cardiovascular problems and cognitive decline.

While outdoor air quality is routinely predicted using advanced models that combine emissions data, chemical reactions, and weather patterns, no equivalent predictive systems exist for indoor environments. This gap presents a major opportunity for innovation.

Indoor spaces are much more controllable and manageable than outdoor environments.  They can be equipped with ventilation systems, active air treatment technologies (e.g. particulate filters, UV disinfection) and sensor networks to monitor and respond to air quality in real time.

However, there’s a critical need to bridge the gap between treatment technology, data acquisition systems, and user experience – and to support transition of buildings to net-zero carbon targets.

This PhD project will tackle that challenge by combining academic expertise in air treatment, sensor systems, and data analytics with industry insights from the iAIR Group and the iAIR Health Labs (formerly Airmid Healthgroup).

The student will work across both Ulster University and industry partners sites, developing and testing sustainable, intelligent air quality solutions.

Using performance data from existing technologies, the project will apply AI and data-driven modelling to predict system efficiency - balancing air purification with energy consumption.

It will also explore how sensor feedback can control treatment systems and communicate indoor air quality metrics to building occupants in meaningful ways.

Why Apply?

  • Tackle a globally relevant health and sustainability challenge
  • Work at the intersection of engineering, data analytics and environmental science
  • Collaborate with leading industry and academic partners
  • Gain experience in AI, sensor integration, and sustainable technology design
  • Benefit from enhanced stipend, and £10k per year additional project funding

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.

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 65%
  • Work experience relevant to the proposed project
  • Publications - peer-reviewed

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:

  • Department for the Economy (DfE)

This scholarship will cover tuition fees and provide a maintenance allowance of £21,000* (tbc) plus £1000 stipend uplift per annum for three years (subject to satisfactory academic performance).  A Research Training Support Grant (RTSG) of approximately £900 per annum is also available.

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.

*Part time PhD scholarships may be available, based on 0.5 of the full time rate, and will require a six year registration period

Recommended reading

World Health Organisation (2024). Ambient (Outdoor) Air Pollution Fact Sheet.  Available online:
https://www.who.int/news-room/fact-sheets/detail/ambient-(outdoor)-air-quality-and-health, Accessed 09/10/25

Lewis AC, Allan J, Carslaw D, Carruthers D, Fuller G, Harrison R, Heal M, Nemitz E, Reeves C, Carslaw N, Dengel A, Dimitroulopoulou S, Gupta R, Fisher M, Fowler D, Loh M, Moller S, Maggs R, Murrells T, … Willis P (2022).  Indoor Air Quality  (Public version, mirrored from www.UK-Air.gov.uk). Department for the Environment, Food and Rural Affairs. https://doi.org/10.5281/zenodo.6523605

World Health Organisation, (2025) Household Air Pollution and Related Health Impacts, Technical document Reference Number: B09440. Available online:
https://www.who.int/news-room/fact-sheets/detail/household-air-pollution-and-health
Accessed 12/09/25

Snelling WJ, Afkhami A, Turkington HL, Carlisle C, Cosby SL, Hamilton JWJ, Ternan NG, Dunlop PSM (2022).  Efficacy of single pass UVC air treatment for the inactivation of coronavirus, MS2 coliphage and Staphylococcus aureus bioaerosols.  Journal of Aerosol Science, Volume 164, 106003. https://doi.org/10.1016/j.jaerosci.2022.106003

Garbagna L, Babu Saheer L, Maktab Dar Oghaz M (2025). AI-driven approaches for air pollution modelling: A comprehensive systematic review. Environmental Pollution, Volume 15; 373:125937. https://doi.org/10.1016/j.envpol.2025.125937

The Doctoral College at Ulster University

Key dates

Submission deadline
Friday 27 February 2026
04:00PM

Interview Date
March 2026

Preferred student start date
14th September 2026

Applying

Apply Online  

Contact supervisor

Dr Patrick Dunlop

Other supervisors