Research Associate/Fellow (Fixed-term)
Project: Deep Learning for Image Analysis
Image analysis is often used to count or measure objects in scientific images. Deep learning has, in the last few years, begun to transform what is possible in the field of image analysis. This is especially true for images containing challenging subject matter. This project will apply and develop cutting-edge machine and deep learning approaches to analyse images from just such a challenging subject: plants. Global food security is an important issue, there is a desire in the agricultural community to automatically measure characteristics of plants, crops and related matter such as seeds automatically to quantify, for example, plant responses to environmental stress (e.g. drought, low nutrients), disease, pests, etc. Recently we have found deep learning to be a promising foundation to help measure such parameters in a high throughput manner (e.g. https://academic.oup.com/gigascience/article/doi/10.1093/gigascience/gix083/4091592/Deep-Machine-Learning-provides-state-of-the-art). This work is vital to finding the high-performing crops needed to feed the population of 9 billion people expected by 2050.
This 3-year project will develop, adapt, and apply deep-learning techniques to a range of plant-derived datasets. These will span from lab-based images, through to glasshouse and field-derived datasets. We will work closely with the project partner Syngenta (www.syngenta.co.uk), a global agricultural company, who will provide the image sets.
The candidate should have a PhD (or be close to completion) in image analysis or a deep learning-related subject, and a desire to push the limits of current deep learning approaches. The ability to work in an interdisciplinary team will be essential. The ability to develop new CNN models/architectures, as well as use existing architectures, will be required.
The candidate will be based in the School of Computer Science, Jubilee Campus at the University of Nottingham, but will be required to spend some time at Syngenta’s international research centre in Berkshire.
This full-time post is fixed-term for a period of 3 years. Job share arrangements may be considered for this post.
Informal enquiries may be addressed to Andrew French, tel: 0115 951 6374 or email andrew.p.french@nottingham.ac.uk. Please note that applications sent directly to this email address will not be accepted.
Further details:
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