Remote or hybrid

CABI Head Office, Nosworthy Way, Wallingford OX10 8DE

Email: A.Szyniszewska@cabi.org

Tel: 07944698117

CABI (Centre for Agriculture and Biosciences International) is an international not-for-profit organization that improves people’s lives by providing information and applying scientific expertise to solve problems in agriculture and the environment. We bring science-based agricultural knowledge to millions of smallholder farmers helping to increase their yields and adopt data-driven approaches to support informed decision making.

CABI is the only organisation worldwide that incorporates a dedicated publishing arm and an independent science media organisation alongside conducting its own scientific research and applying practical expertise in digital and other approaches to reach farmers and other stakeholders.

Digital Development in CABI is comprised of several themes of work, including Data Policy and Practice, Digital Advisory Tools, and Modelling and Data Science. Under Modelling and Data Science, the Global Burden of Crop Loss (GBCL) initiative is an ambitious global research collaboration that will support informed action to reduce crop loss globally.

An internship with CABI and the GBCL team will be a highly rewarding experience to help develop the proof-of-concept estimates on wheat loss and economic burden globally, for at least one year on a country/regional level. This is an exciting time for GBCL – we are rapidly forming partnerships, developing solutions, and refining our analytical framework. Interns will therefore be able to have a strong contribution to a highly ambitious initiative that aims to have a transformative impact on plant health.

The global challenge of crop loss

The impacts of biotic and abiotic factors on crop yield are significant, with around 20-40% of the world’s major crops lost to pests alone (Savary et al. 2019). While it is clear that crop loss causes significant impacts on food systems globally and that reducing losses represents a major opportunity to increase yields with minimal environmental impact, we lack robust evidence on the problem to mobilize action. Data on the scale, scope, spatial patterns, and drivers of loss are outdated, lacking in granularity, not shared, or missing altogether. Scientists often focus on a limited number of pests and geographies and often work in isolation, resulting in small pockets of disconnected information that are often not easily accessible to other researchers and decision makers. Without knowing how much of our food supply we are losing, where we are losing it, and what we are losing it to, actors across the plant health system lack clarity on how to take effective action and on which interventions to prioritise.

Internship

The 3-month internship may involve various aspects of technical development across the GBCL initiative. Which areas you may focus on will be mutually agreed during the application process. There are many exciting areas you could be involved in, including: modelling the impact of biotic and/or abiotic factors on crop losses, supporting the development of crop growth models, developing layer representing predominant global farming systems, and much more! The themes of our analytical framework include:

· Attainable yield in context

. Actual crop production and yield

· Yield loss

· Apportioning losses: biotic vs. abiotic

· Costs of control

· Burden

This internship would suit a student who is interested in developing their data analysis and technical skills, and who is interested in the interface between science, policy, and decision-making. Please note, if you are specifically interested in working with crop growth models, specifically the impacts of extreme weather on crop yields, there is scope to undertake a joint internship with CABI and Assimila (www.assimila.earth). Assimila use satellite data and weather information to address real world problems. They work closely with leading universities and institutions to translate cutting edge research into practical applications, developing innovative techniques to transform data into useful information for sustainable environmental management.

Essential skills

· Knowledge of plant health or agricultural systems

· Data analysis, visualisation, and reporting

· Spatial analysis/GIS

· Proficiency in at least one statistical programming language, such as R or Python

· Investigative and analytical with a willingness to embrace new approaches and technology

· Good quantitative skills (maths or statistics)

· Curious and creative

· Flexibility when faced with change

· Accurate; attention to detail and quality

Desirable experience

· Experience with crop statistics and crop growth models

· Experience using earth observation data

· Working knowledge of crop pests and pathogens