HAU Annual DVC Funded PhD Studentship: Aerial Very- and Ultra-Low Volume Variable Rate Spraying for Autonomous Arable Systems

This project is one of five opportunities being advertised by Harper Adams University as part of our annual competition for a funded PhD studentship. The successful candidate will receive a studentship consisting of full tuition fee coverage, a stipend and approved research costs.

Aerial Very- and Ultra-Low Volume Variable Rate Spraying for Autonomous Arable Systems

Autonomous arable farming has advanced significantly through the Hands-Free Hectare and Hands-Free Farm initiatives, demonstrating that crops can be established, managed and harvested without in-field human operators. These systems integrate GNSS-guided machinery, remote sensing and data-driven decision-making to deliver commercially viable yields. However, crop protection remains largely dependent on conventional ground-based spraying, limiting operational flexibility and environmental optimisation.

Unmanned aerial vehicles (UAVs) are increasingly used globally for pesticide applications, enabling highly targeted interventions, reduced operator exposure, and significantly lower pesticide use. Despite this, there is limited understanding of UAV spray behaviour under temperate UK very-low volume and ultra-low volume formulations operating conditions and no fully integrated framework linking UAV-based sensing, decision-making and variable-rate aerial application within autonomous farming systems.

This research studentship will address the challenge of integrated UAV-based variable-rate spraying system for autonomous arable production. The project combines hyperspectral sensing, machine learning, and spray physics solutions to the emerging area of precise, data-driven crop protection.

The research will have access to in-house and external partner spray labs, the Hands-Free Farm, a soil hall and the UK government agency governing UAV sprays.

Academic Requirements

Required degree level: A first-class or strong upper second-class undergraduate degree (or equivalent) in Agricultural Engineering, Biosystems Engineering, Mechanical Engineering, Environmental Engineering, or a related discipline

Additional skills required:

• Strong analytical and quantitative skills.
• Excellent written and spoken English communication skills.

Desirable (but not essential):

• Knowledge of fluid dynamics, especially experimental methods in atomisation and sprays.
• Programming experience (e.g. Python, MATLAB or similar).
• Experience with data analysis, machine learning or geospatial datasets.
• Experience with UAVs, precision agriculture or remote sensing.
• Experience with writing for publications.