Crop Development Modeller - KTP Associate (fixed term) (SCI173918X1)

The UK Vining Pea Industry is world-leading. An exciting opportunity is available to design and develop methods for timely forecasts to transform the efficiency of harvesting and processing of vining peas. This position is part of a Knowledge Transfer Partnership (KTP) between PGRO and Nottingham University and will be based at PGRO (Peterborough) with some time spent at project partners Bird’s Eye and Nottingham University. The position will involve the analysis, interpretation and collection of data through interactions with growers and provides a great opportunity to work at the interface of science and practice.

PGRO is funded by growers in order to deliver innovative tools & techniques for practical application by the industry to improve crop profitability. A step change in harvest and processing efficiency is a key requirement for the industry and this project will address this through the use of data and model analytics to improve yield and quality forecasting in advance of harvest. Data sources will be a combination of direct field and remotely sensed measurements. To achieve this objective, PGRO has partnered with the quantitative agricultural research expertise of the University of Nottingham and the industry leading production and processing expertise of Bird’s Eye. The post provides outstanding career development opportunities through both formal training and the experience that the role holder will gain.

Knowledge Transfer Partnerships are a government funded knowledge transfer initiative that support partnerships between business and universities, placing graduates with exciting and high profile projects.Further information is available at: www.facebook.com/uonktp

Candidates for this post should have:

Candidates should have a BSc in a relevant subject area; candidates with post-graduate experience and/or qualifications such as MSc & PhD in relevant subject areas are welcome.Relevant and applied practical experience in statistical and computational modelling techniques, including simulation models, regression and data visualisation.Knowledge or experience of the application of remotely sensed measurements to agriculture is desirable but not essential. Background knowledge of the agriculture industry is desirable but not essential.Excellent analytical and problem solving skillsAbility to work independently (including travel to remote field sites which will require driving), prioritise tasks and work to tight deadlines.Good project management skills.Good interpersonal and communication skills and the ability to deal with a variety of people at different levels.Willingness to be available outside of normal working hours at times, particularly during the cropping season

The role is available as a 36 month fixed term KTP Associate contract. 

For further information please contact neil.crout@nottingham.ac.uk. Please note that applications sent directly to this Email address will not be accepted.

Closing Date: 28 Sep 2018
Category: Research and Teaching (R&T)