PhD Opportunities

The Agricultural Robotics and Engineering Group at the University of Bonn is conducting world-class research in the area of Robotic Vision to enable Robots and Autonomous systems to be deployed in challenging real-word environments.

There is currently an opening for two PhD positions to work in the area of agricultural robotics to enable precise intervention in the field. Both positions will develop novel robotic vision methods to understand the complicated agricultural environment to enable precise intervention (action) within the field. The first position will concentrate on developing novel methods to perform precise and accurate management of individual weeds. The second position will develop novel methods applicable to precision horticultural management; interacting with the plant and crop. More details for each project can be found below.

Robotic Weed Management enabled by Vision

There is currently an opening for a PhD student to work in the area of integrated weed management enabled by robotics and robotic vision. Precise weed management in a farm could revolutionise agricultural practices. This project will consider novel methods to perform precise and accurate management of individual weeds in real farm environments enabled by fine-grained image classification capable of being deployed in challenging environments. The ideal candidate will be hands-on and have a strong desire to see their work deployed on a functioning robotic system. They will have strong programming skills (preferably in C/C++ or Python), an interest in Computer Vision/Deep Learning and experience with ROS.

This PhD is supported by the PhenoRob Cluster of Excellence and the successful candidate will be an active contributor within the Cluster of Excellence.

All applications should be sent directly to me. Applications will close by September 15th, at the latest.

Robotic Vision for Precision Intervention in Horticulture

There is currently an opening for a PhD student to work in the area of agricultural robotics for detection and interaction with crops in horticulture, to enable precise intervention in the field. Detecting occluded crops is a key element for automating horticulture and a very challenging computer vision problem. This project will explore novel methods to perform segmentation and detection of occluded crops using through colour, depth and multi-spectral imagery. An important aspect of this project will be to deploy the developed algorithms on a robotic system to interact with the crop. The ideal candidate will be hands-on and have a strong desire to see their work deployed on a functioning robotic system. They will have strong programming skills (preferably in C/C++ or Python), an interest in Computer Vision/Deep Learning and experience with ROS.

All applications should be sent directly to me. Applications will close by the 1st of September.