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Development of optimal lighting system to improve crop productivity

  • Full or part time
  • Application Deadline
    Friday, May 29, 2020
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

Project Description

Coventry University (CU) is inviting applications from suitably-qualified graduates for a fully-funded PhD studentship for doctoral projects that support Global Challenges (GCRF) and UN Sustainable Development Goals. The successful candidates will be joining the project “Design optimal lighting system for improved crop productivity.”

An organism’s biological clock called the circadian system, is vital for optimal biological functions coordination. In plants, the circadian system is responsible for crop productivity-related functions (e.g. flowering and hypocotyl growth). Recent advances in the area of plant circadian system have shown that the use of different light colours can improve crop productivity. However, a systematic characterisation and framework on light properties (e.g. intensity, photoperiod) leading to optimal crop productivity is still lacking.

This project aims at enhancing plant growth and productivity by developing a framework of optimal lighting system that is simple, cost-effective and energy-efficient to implement. This will be achieved via the development and validation of a computational model of plant circadian system based on the influence of light colours on plant growth. The model will be used for scenario simulations to establish a framework of optimal light regulation, which will be used to design an optimal lighting system on a lab scale as initial proof-of-concept.
The bespoke cost-effective lighting system that will be developed will support to achieve better crop productivity, thus aligning with the GCRF strategy of global access to sustainable agriculture and UN SDG Goal No. 2 of achieving zero hunger.

Start Date: September 2020

Duration of Study: Full-Time – between three and three and a half years fixed term

Training and Development

The successful candidate will receive comprehensive research training including technical, personal and professional skills.
All researchers at Coventry University (from PhD to Professor) are part of the Doctoral College and Centre for Research Capability and Development, which provides support with high-quality training and career development activities.

Entry requirement

• Successful candidate will have at least a minimum of a 2:1 first degree in Control/Electronics/Electrical/Mechanical Engineering, Mathematics or a related discipline (and preferable a Master degree)
• A minimum of English language proficiency (IELTS overall minimum score of 7.0 with a minimum of 6.5 in each component)
• Real passion for plant biology and would like to be involved in building cutting edge technology in the area of application engineering to smart farming.

Desired Skills

Mathematical modelling:
Knowledge of tools and techniques required for developing mathematical model is essential while modelling knowledge related to plant biology would be desirable.

Experience of programming in MATLAB/Simulink, Python, C++ or similar languages. The candidate should be able to understand software and hardware integration requirements.

Experience in building simple circuits, reading circuit schematic and soldering skills would be desirable.

Excellent communication skills and an ability to interact professionally and productively with other team members. The candidate should be able to present well, plan, be confident and proactive. The candidate is expected to take initiative in planning and executing experiment with minimal supervision.

For further details see:

To apply on line please visit:

All applications require full supporting documentation, a covering letter, plus a 2000-word supporting statement showing how the applicant’s expertise and interests are relevant to the project.

Funding Notes

The studentship will pay an annual stipend at the standard UKRI rate and covers 100% tuition fees at the UK/EU/International rate for 3.5 years.

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