Engineering Doctorate – Autonomous systems for aquatic plant detection and classification

You will design, prototype, and validate an automated system for detecting and mapping aquatic vegetation using multimodal sensor data collected from UAVs and surface platforms. Working in real canal environments characterized by turbidity shifts, wind-generated ripples, glint, and diverse plant morphologies, you will:

Design and implement a multimodal sensing payload (HSI + polarimetry) on existing UAV platforms
Conduct controlled lab experiments to characterize spectral-polarimetric traits of aquatic vegetation
Deploy and optimize the system in Dutch canal field sites with operational partners
Develop calibration, co-registration, and water-column compensation routines
Build a supervised ML pipeline to classify invasive vegetation
Produce geospatial output layers compatible with waterboard GIS infrastructures
Translate requirements from ecological, municipal, and industrial stakeholders into engineering specifications
Perform structured verification and validation following the systems engineering V-model

Rather than pursuing purely fundamental research, this EngD emphasizes iterative prototyping, verification and validation, traceable requirements, and translation of sensor outputs into actionable stakeholder insights. Field deployment under real conditions is a core component of your work.