Scholarship

Optimisation of Light Sources

University of Leeds Original Source

About This Opportunity

This fully funded PhD position at the University of Leeds investigates how the spectral characteristics of light can be optimised for visual inspection tasks, and how different lighting conditions influence human visual performance. The project examines spectral tuning and optimisation techniques using advanced LED lighting systems, human colour perception and task performance under different spectral conditions, applications across various sectors (healthcare, textiles, cosmetics) where accurate colour discrimination is essential, and potential enhancements for colour-deficient observers. The research draws on advances in spectrally tunable lighting and low-cost programmable LED systems, with experimental work conducted in the School of Design's lighting laboratory. The project forms part of the LITAC Studentship and benefits from strong academic and industrial collaborations including partners from University of East Anglia, University of Cambridge, University of Sussex, Apple, Verivide, and the Society of Dyers and Colourists. The successful applicant will join the Leeds Institute of Textiles and Colour (LITAC), a collaborative international research institute focused on addressing global challenges and sustainable development in textile and colour industries. The award provides full academic fees, a maintenance stipend (£20,780 in 2025/26), and an additional £10,000 LITAC grant spread over the period of study for outcome dissemination, personal development, and research consumables.

36 - 37 mo
1 awards
Renewable (2yr)

Who Can Apply

Region
United Kingdom
Citizenship
United Kingdom
Residency
United Kingdom
Project in
United Kingdom
Applicants
individual

Application Details

Stages

  1. 1 two_stage

Required documents

cv transcripts research_proposal references

Review process

Two-stage process: first apply for research place of study through online application, then complete scholarship application form. Selection based on academic merit.

Additional benefits

  • training
  • equipment

Restrictions

  • geographic_restrictions
  • reporting_requirements