Back to search results

PhD Studentship: CominingCropQuant Phenotyping Robot and AI Technologies to Gain Insights of Wheat GxE Interactions in Changeable Environmental Conditions (ZHOU_E19DTP)

University of East Anglia - School of Computing Sciences

Qualification Type: PhD
Location: Norwich
Funding for: UK Students, EU Students
Funding amount: £14,777 per annum
Hours: Full Time
Placed On: 10th October 2018
Closes: 26th November 2018

Location Earlham Institute, Norwich
Start date: 1/10/2019
Closing date: 26/11/2018
No. of positions available: 1
Hours: Full-time
Contract: Temporary
Supervisor Ji Zhou

Project description

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.

Person Specification UK 2:1 & English Language (6.5 overall, 6 in each section)

Funding notes For funding eligibility guidance, please visit our website: Full Studentships cover a stipend (UKRI rate: £14,777pa – 2018/9), research costs and tuition fees at UK/EU rate and are available to UK and EU students who meet the UK residency requirements.  

Students from EU countries who do not meet the UK residency requirements may be eligible for a fees-only award. Students in receipt of a fees-only award will be eligible for a maintenance stipend awarded by the NRPDTP Bioscience Doctoral Scholarships. To be eligible students must meet the EU residency requirements.  

This project has been shortlisted for funding by the Norwich Biosciences Doctoral Training Partnership (NRPDTP). Shortlisted applicants will be interviewed as part of the studentship competition. Candidates will be interviewed on either the 8th, 9th or 10th January 2019. 

The NRP DTP offers postgraduates the opportunity to undertake a 4-year research project whilst enhancing professional development and research skills through a comprehensive training programme. You will join a vibrant community of world-leading researchers. All NRPDTP students undertake a three-month professional internship (PIPS) during their study. The internship offers exciting and invaluable work experience designed to enhance professional development. Full support and advice will be provided by our Professional Internship team. Students with, or expecting to attain, at least an upper second-class honours degree, or equivalent, are invited to apply. 

 For further information and to apply, please visit our website: 

We value your feedback on the quality of our adverts. If you have a comment to make about the overall quality of this advert, or its categorisation then please send us your feedback
Advert information

Type / Role:

Subject Area(s):


PhD tools
More PhDs from University of East Anglia

Show all PhDs for this organisation …

More PhDs like this
Join in and follow us

Browser Upgrade Recommended has been optimised for the latest browsers.

For the best user experience, we recommend viewing on one of the following:

Google Chrome Firefox Microsoft Edge