Post-Doc position Innovative Automated Pest Monitoring using machine vision on UAV image data
The laboratory of Geo-Information Science and Remote Sensing is offering a 17 month Post-Doc position to develop an efficient and accurate monitoring system to identify the presence of Drosophila suzukii - also known as Spotted Wing Drosophila - flies in fruit orchards. The first step in controlling D. suzukii and preventing crop damage is recognising that the fly is present. A novel system will capture very high-resolution images of insect traps by means of an Unmanned Aerial Vehicle (UAV) and these will be analysed in an automated image processing pipeline for the identification and counting of the number of D. suzukii per trap location.
The Post-Doc will focus on: 1) the design, development and evaluation of machine vision methods for identification and counting of specific insects from very-high resolution optical images acquired with Unmanned Aerial Vehicles (UAVs); and 2) development of a Decision Support System (DSS) using georeferenced insect counts as a basis for a GIS-based system giving farmers the possibility to incorporate data directly to their precision farming platforms.
The research is part of the Unmanned Aerial Remote Sensing Facility (UARSF) of Wageningen University and Research which aims at developing innovation in the field of UAV remote sensing science by providing a platform for dedicated and high-quality experiments. The facility has a large range of platforms and camera systems available, and consists of an interdisciplinary team of researchers focussing on solutions for scientific challenges but also looking forward to value adding products and services. The Post-Doc will be working within the project 'Automated Airborne Pest Monitoring of Drosophila suzukii in Crops and Natural Habitats' funded from the Era-net program Integrated Pest Management. Within the project there will be cooperation with partners in Switzerland and the United Kingdom. We are looking for a creative and independent researcher with a PhD degree and related experience in remote sensing, machine vision, artificial intelligence and/or computer science. We ask for a background and track record of peer-reviewed publications in remote sensing, object-based image analysis and machine vision in environmental applications. The postdoc should contribute to the image processing workflows and implement algorithms in relevant (open source) software and programming environments (e.g., Matlab, R, Python). Experience with designing, managing and executing field experiments, and operational knowledge of UAV based systems is an asset. As you will be working in an interdisciplinary team in international cooperation with universities, research organizations and companies, we expect a pro-active and collaborative attitude and excellent communication skills both in presentations and writing.
This job comes from a partnership with Science Magazine and