We are currently advertising National Productivity Investment Fund Industrial CASE studentships with a deadline of the 16th July 2018.

27 / 06 / 2018

Using deep learning and AI to tackle global food insecurity and undernutrition (ZHOU_E18ICASENF)

how to apply

A machine learning (ML) or artificial intelligence (AI) PhD does not only open up some of the top-paying jobs in many industrial sectors, it also prepares you for the future challenges in our changing world. ML techniques allow you to generate rules that were learned from experience rather than directly programming, a revolutionised approach which could be used to address the global food security challenge that we will have to face in the near future. It's a hot field and some hype is true – powerful AI systems could accurately extract specific features from crop plants as well as monitor how our crops are performing under different environments. But the technology is far from perfect, the negatives include the need of huge training datasets, overfitting for specific tasks, and catastrophic failure if the model has not seen exceptional datasets. Hence, you could have much positive impact 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 machine learning skills you can gain in a PhD. You can help shape this powerful technology and apply it to food security problems. The industrial partner for this project is Syngenta.