SimFarm 2030: An empirical, data driven, model for wheat cultivars and optimisation for future climate scenarios (2020)

What you get

The stipend is at standard Research Council rates. A bursary of £15,285 is available as well as a waiver of tuition fees.

Type of award

Postgraduate Research

PhD project

Appropriate new crop cultivated varieties, or cultivars, are essential in addressing future food demands in a changing climate, reducing crop fertilizer and water demand and vulnerability to adverse climatic events such as heatwaves, drought or flooding. In contrast, poorly suited cultivars could lead to crops with low environmental efficiency and highly variable yields affecting sustainability and food security.

The project will apply Bayesian Hierarchical probabilistic techniques to empirically model the yield of wheat cultivars as a function of deterministic variables. This will enable forecasts and hypothetical experiments that will in turn provide decision support and help optimise selection of current and future wheat cultivars for UK conditions and future climate forecasts.

The key input variables will include meteorological variables (temperature, precipitation) and environmental variables (pollution, soil characteristics). The project’s approach will be complementary to process-based physiological crop models but will be less constrained to specific lab-based models and so will be more adaptable. The model will be flexible to permit consistency with the best available data from the Agriculture and Horticulture Development Board (AHDB) (i.e. calibrated or "trained") while being designed to fit within broad physiological constraints. The Hierarchical Bayesian approach ensures adaptability and an intrinsic and rigorous calculation of uncertainties in predictions.

What kind of applicants are we looking for?

Your application should demonstrate adaptability and enthusiasm for inter-disciplinary research, and evidence of strong quantitative skills e.g. a degree focused on applied mathematics, physics, or computing, or use of advanced quantitative techniques or programming in a biology or ecology degree.

Supervisory team:

This PhD project is an unusual interdisciplinary enterprise, supervised jointly by an astronomer with extensive data science skill and a crop scientist. The project follows on from successful

pilots funded by the STFC Food Network+ https://www.stfcfoodnetwork.org/. 

The main project supervisory team consists Prof Seb Oliver (University of Sussex), an astronomer with recent experience translating quantitative skills into health, Earth observation and biosciences, and Dr Jake Bishop (University of Reading), a crop scientist with expertise in climate factors driving crop productivity. We have recently worked together on a project SimFarm 2030 and this PhD represents the development of those ideas and methodologies.

Additional Support and Training

Alongside academic supervisors the student will also receive regular support from Dr Ed Pope at the UK Met Office, and is expected to undertake a placement provided by Quant Foundry, and will be linked closely with the agricultural industry via regular reporting to, and input from, AHDB, the UK crop levy board. The successful student would be expected to join the Data Intensive Science Centre (DISCnet www.discnet.org.uk) a centre for doctoral training that was rated "A" in a review by the Science Technology and Facilities Council (STFC).

Further reading:

The project will continue to develop methods used in a recent STFC projects FACYnation and SimFarm 2030, see Shirley et al. 2020. doi.org/10.1088/2515-7620/ab67f0. The project will integrate crop science knowledge, see Harkness et al. 2020 doi.org/10.1016/j.agrformet.2019.107862

Start Date:

The start date is expected to be September 2020 to fit with the normal academic year and benefit from the 1st year of DISCnet training.  However, the start date is flexible

Eligibility

Due to funding limitations, this project provides a fee waiver for UK and EU students only.

Applicants must hold, or expect to hold, a UK Bachelor degree in a relevant subject with first class Honours, (or an EU equivalent degree). Alternatively, a UK second-class Bachelor degree plus a UK Masters degree at Merit classification (or an EU equivalent).

Candidates should have a strong background in a quantitative science such mathematics, physics, computer science. Candidates for whom English is not their first language will require an IELTS score of 6.5 overall, with not less than 6.0 in any section.

Deadline

How to apply

Apply via the Sussex online system at

https://www.sussex.ac.uk/study/phd/apply/log-into-account

Apply for a place on the PhD in Physics with a start date of September 2020.  Include a CV, your degree transcripts and certificates, the names of two academic referees, and a statement of interest.

In the Finance/Funding section of the online form, state that you are applying for the SimFarm 2030 project supervised by Prof Oliver and Dr Bishop.

Contact us

For enquiries about the application process contact: mpsresearchsupport@sussex.ac.uk.

For enquiries about the project contact Seb Oliver S.Oliver@Sussex.ac.uk