Developing CropQuant Phenotyping Robot and AI Technologies to Gain Insights of Wheat GxE Interactions in Changeable Environmental Conditions (ZHOU_E19DTP)
- Research Area Agriculture and Food Security
- Partner The Earlham Institute (EI)
Dr Ji Zhou -
- Application Deadline 26/11/2018
A machine learning (ML) or artiﬁcial intelligence (AI) PhD is likely to prepare you for the future challenges in this changing world. It can open up some top-paying jobs in industrial sectors such as ﬁnance, gaming and research. ML techniques allow you to generate very complicated rules through dynamic programming, an approach which is now being used to address the global food security challenge due to the changeable environments. In this project, we will utilise the latest open-source ML techniques to extract meaningful information from large-scale phenotype and environment datasets; develop advanced AI methods to navigate CropQuant robot to travel in the wheat ﬁeld; exploit powerful embedded AI systems (e.g. Intel’s Movidius NCS technologies) to link crop information, climate patterns, and phenotypic traits to gain insights of how our crops are performing under rapidly changing agricultural environments. Because the AI technology is far from perfect, you could therefore have positive impacts on our future work in crop research, the friendly supervisory team will provide comprehensive guide on ML to help you get started. The outstanding lab members will assist you with the ML/AI skills you can gain in a PhD. You can help shape this powerful technology and apply it to resolve real-world food security problems. The industrial partner of this PhD project is Intel UK.