PhD Studentship in Agricultural, Environmental and Food Economics by Distance (full-time)

Updated: about 2 years ago
Location: Reading, ENGLAND
Job Type: FullTime
Deadline: 02 Apr 2022

Project title:  Assessing current adoption and potential for future Integrated Pest Management (IPM) on Irish grassland farms (Walsh Scholarship Ref Number: 2021037)

Department/School: School of Agriculture, Policy and Development (SAPD)

Supervisors:  Philip Jones (SAPD), Stephen Kildea and Fiona Thorne (Teagasc)                                                                                                                       

Project Overview:   The University of Reading is offering a funded 4-year PhD programme, tied to a separately-funded research project managed by Teagasc, Ireland, and funded under the Teagasc Walsh Scholarship programme. The Teagasc project addresses the issue of uptake of Integrated Pest Management (IPM) for grassland on Irish farms. This will involve: (a) consulting stakeholders to evaluate current pesticide use; (b) creating a metric for measuring IPM across grassland systems; (c) identifying approaches to increase use of IPM and quantifying progress over time; and (e) determining impacts of IPM adoption on economic, social and environmental sustainability. The candidate will undertake elements of this project research to supplement their own PhD research programme. The student will be registered at the University of Reading, UK, but will be largely based in Ireland working alongside Teagasc staff. Some time each year will be spent in Reading for supervision and training purposes.

Experience with data collection, data management and interaction with industry stakeholders/farmers would be an advantage.

Eligibility: 

  • Applicants should have a master’s degree in: agricultural science, geography, business, economics or related fields, and have a good knowledge/interest in grassland systems. Candidates with an upper second-class honours undergraduate degree will be considered if they can demonstrate relevant post-degree work or research experience.
  • Applicants whose first language is not English require a minimum IELTS score of 6.5. Further information on English language requirements will be provided on application.
  • This This is a 4 year fully-funded PhD scholarship covering fees at Republic of Ireland/UK rate. International candidates are welcome to apply, however they would be required to fund the difference between Republic of Ireland/UK and International tuition fees.

Funding Details:   

  • The scholarship funding is €24,000 per annum and includes contribution to university fees of up to a maximum of €6,000 per annum and is tenable for four years.

How to apply:   

To apply for this studentship please submit an application for a PhD in Agricultural Economics at http://www.reading.ac.uk/graduateschool/prospectivestudents/gs-how-to-apply.aspx . 

*Important notes*

  • 1) Please quote the reference ‘GS21-021’ in the ‘Scholarships applied for’ box which appears within the Funding Section of your on-line application.
  • 2) The studentship does not require the applicant to upload a project proposal, however, candidates are asked to supply (i) a curriculum vitae (including contact details for at least one academic referee); and 2) a covering letter (less than 800 words) detailing qualifications and experience and indicating the relevance of your degrees to the topic, as well as your academic strengths, personal attributes and career aims as they align to the PhD topic.

Application Deadline:  2nd April, 2022.

Shortlisted candidates will be interviewed during the last week of April 2022.

Further Enquiries:  

For further details about the PhD programme, contact Karen Garrod at [email protected]

For further details about the Teagasc project, contact Fiona Thorne at [email protected]

Please note that, where a candidate’s application is successful, this will be confirmed via: a formal studentship award letter and a separate Offer of Admission, subject to standard checks for eligibility and other criteria.