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  1. Queen Mary University of London
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  6. Leverhulme Living With Waste Doctoral Programme
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  8. 2026 4-year call
  9. Drone-Integrated High-Frequency Dielectric Sensing

Drone-Integrated High-Frequency Dielectric Sensing

 

Drone-Integrated High-Frequency Dielectric Sensing for In Situ Monitoring of Emerging Waste in Freshwater Systems

Lead Supervisor: SaeJune Park

Website • Email

Degree Programme: PhD in Electronic Engineering

Co-Supervisors:

Ketao Zhang (School of Engineering and Materials Science)

Iwan Jones (School of Biology and Behavioural Sciences)

Project Description

Pollution from historical landfills, industrial outfalls, and mines continuously discharges complex mixtures of toxic heavy metals and degraded plastics into river networks. Conventional monitoring relies on manual grab-sampling followed by laboratory analysis, which is labour-intensive, hazardous, and unable to capture transient contamination. This project addresses a fundamental scientific question: How can high-frequency electromagnetic resonance be integrated with autonomous physical sampling to quantify trace contaminants in situ across dynamic hydrological interfaces? Resolving this question requires an essential three-way cross-disciplinary framework:

  1. High-frequency sensor physics (EECS): Planar microwave resonators provide label-free dielectric sensitivity to trace contaminants in water, avoiding the biofouling issues of conventional sensors.
  2. Aerial-surface mechanics (SEMS): Multimodal amphibious drones navigate fragmented reaches and land on water for contamination-controlled autonomous fluid sampling.
  3. Freshwater ecology (SBBS): Catchment biomonitoring expertise translates raw dielectric signals into meaningful ecological risk indicators. 

The doctoral researcher will focus on three connected objectives:

  1. [Months 0 to 18] Design planar microwave metamaterial resonators coupled with microfluidic channels using 3D simulations for trace contaminant detection.
  2. [Months 19 to 24] Interface sensors with compact, low-cost nano-VNAs and onboard processing to create an ultra-lightweight payload.
  3. [Months 25 to 36] Integrate the payload onto an amphibious drone for autonomous flight, water landing, and field validation.

Shaping Your Research:

We encourage applicants to bring their own research vision to the project. Depending on your background, there is flexibility to shape key directions, including:

- Developing novel metamaterial topologies or expanding into terahertz sensing regimes for priority emerging pollutants.

- Implementing onboard machine learning models for real-time dielectric signal decomposition.

- Tailoring drone sampling mechanics or targeted ecological validation across UK river catchments.

This establishes a closed loop between physical sensing, aerial robotics, and field ecology for adaptive waste monitoring.

What we're looking for in a student

Applicants should hold, or expect to obtain, a first-class or good upper second-class honours degree (or equivalent master's degree) in Electronic Engineering, Electrical Engineering, Physics, Applied Physics, Robotics, Mechatronics, or a closely related physical science discipline. A solid foundation in high-frequency electromagnetics, RF circuits, or sensor systems is desirable, alongside an enthusiasm for multidisciplinary research bridging hardware engineering and environmental applications. Practical experience with numerical electromagnetic simulation tools (such as CST Studio Suite or COMSOL) or hands-on prototyping is advantageous. The successful candidate will join the Centre for Electronics in EECS and benefit from co-supervision across SEMS and SBBS. You will receive comprehensive training in high-frequency measurement, microfabrication, autonomous aerial robotics, and aquatic ecological field sampling methods.

 

Key words: Microwave; Metamaterials; Resonators; Sensing; Microplastic

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