About this role
Full time: 35 hours per week
Fixed term: 3.5 years
The opportunity:
SEBI-Livestock (hereafter SEBI-L) is a dynamic and innovative organisation tasked with improving livestock data and evidence in low- and middle-income countries to support better informed decision making. We provide core data and monitoring services to the Bill & Melinda Gates Foundation (BMGF) to assist in the tracking of their livestock investments. In addition, we convene a large livestock data network, Livestock Data for Decisions (LD4D), to help achieve common goals.
The post of Research Assistant (Livestock Insights & Modelling) will sit within the Insights and Modelling Group and will support SEBI-L efforts to develop and improve models to support decisions. This will include the improvement of a livestock health and production evidence base through reviewing existing sources of evidence (e.g. literature, systematic reviews). This evidence base will create datasets to support mathematical models as well as delivering insights for decision makers (such as BMGF). The post holder will also produce manual outputs to support the development of SEBI-L’s automated systematic mapping tool, LitXpress. This post is suitable for a diligent and service-focused individual with excellent attention to detail.
This post is full-time (35 hours per week); however, we are open to considering part-time or flexible working patterns. We are also open to considering requests for hybrid working (on a non-contractual basis) that combines a mix of remote and regular on-campus working.
The salary for this post is £34,610 to £39,906 per annum.
Your skills and attributes for success:
Educated to degree level or above in a relevant subject e.g. biological sciences / animal production / health / veterinary science / epidemiology/ livestock or agricultural economics Knowledge and experience in the application of systematic literature reviews Ability to work in a multidisciplinary team as well as independently Strong interpersonal skills and ability to foster collaborative relationships Combines strong attention to detail with practical, service-focused problem-solving