Food Security Now! Mining Data on Insect Ecology to Create More Sustainable Pest Control Management (Distance Learning Project)

University of Aberdeen

School of Biological Sciences

Project Description

Human populations are growing at a faster rate than ever. The UN has announced that food production in its current form will not manage to feed the human population if it continues to grow. This global crisis is exacerbated by insect pests, which causes major economic harm to countries worldwide by decreasing food yield from crops. Food security is therefore a major bottleneck for human survival and prosperity, especially in the developing world. New ways to mitigate the threat imposed by insect pests are therefore urgently needed. We are advertising a Distance Learning PhD project to investigate this problem and provide solutions.

The student will gather disparate information in the fields of insect developmental ecology, applied pest management, economics, and agriculture to create innovative data-driven pest control solutions that can be implemented in the field to increase food security worldwide. For example, using public ecological data, it is possible to identify the underlying molecular pathways that stop pests from laying eggs in certain plants. This information can then be used to develop new environmentally-friendly products (e.g., environmentally-friendly compounds) that repel females from laying eggs on the crop of interest – i.e., ‘mimicking pesticide’. In doing so, the project addresses major ongoing yet unresolved issues of insect pest control, and therefore has broad appeal to both fundamental and applied sciences, as well as to policy decisions at local, national, and international conferences. The scope of the project can be agreed upon, but the project strongly encourages students to focus primarily on challenges posed by insect pests to the most vulnerable communities (e.g., developing countries).

Food Security Now! is primarily designed to be desk-based, where the student will make use of the unprecedented number of datasets available in the public domain, synthesise existing knowledge, create new solutions, and if possible, test the solutions using modelling and/or field data available through third parties (e.g., companies, growers etc). We are also open to the possibility of the student conducting their own field experiments; this can be discussed with supervisors depending on the progress of the project. The project will be conducted primarily as Distance Learning, allowing the student to undertake the project away from the University of Aberdeen. Students will be in regular contact with their supervisory team by Virtual Conference and encouraged to visit Aberdeen if feasible. The student will be supported by regular meetings with the supervisors and through social events with other graduate students within SBS. Within the group, the student will have the opportunity to develop quantitative skills through online/MOOC courses in platforms such as DataCamp and Coursera and writing skills for academic audiences, policy-makers, and general public. The student is expected to engage in outreach projects in their home country and/or in countries where the findings of the project are likely to have the most impact on vulnerable communities (e.g., subsistence farmers).

Funding Information

This PhD project is only open to sponsored students and those who have their own funding. Supervisors will not be able to respond to requests to source funding.

Eligibility Requirements

The successful applicant will have a high level of self-discipline to work long-periods of time at home, showing strong commitment to the project and understanding the broad impacts of the project to the wider community. Willingness to learn new skills and make an impact in local communities are essential. Quantitative skills are not mandatory, although the applicant should be passionate about the opportunity of working with data science.

Application Process

To submit an application please visit our Website
-Apply for ‘PhD in Biological Science’
-State the name of the lead supervisor on your application
-State the name of the project

Please note that we will not proceed with applications that have not stated their intended funding source. Applicants will be expected to have suitable computing materials to enable them to work from home at a distance to undertake this project.


Bianchi, F.J., Booij, C.J.H. and Tscharntke, T., 2006. Sustainable pest regulation in agricultural landscapes: a review on landscape composition, biodiversity and natural pest control. Proceedings of the Royal Society B: Biological Sciences, 273(1595), pp.1715-1727.

Lang, Tim, and David Barling. “Food security and food sustainability: reformulating the debate.” The Geographical Journal 178, no. 4 (2012): 313-326.

Lewis, W.J., Van Lenteren, J.C., Phatak, S.C. and Tumlinson, J.H., 1997. A total system approach to sustainable pest management. Proceedings of the National Academy of Sciences, 94(23), pp.12243-12248.

Pickett, J.A., Wadhams, L.J. and Woodcock, C.M., 1997. Developing sustainable pest control from chemical ecology. Agriculture, ecosystems & environment, 64(2), pp.149-156.

Schetelig, M.F., Lee, K.Z., Otto, S., Talmann, L., Stökl, J., Degenkolb, T., Vilcinskas, A. and Halitschke, R., 2018. Environmentally sustainable pest control options for Drosophila suzukii. Journal of applied entomology, 142(1-2), pp.3-17.

To apply for this PhD, please use the following application link: