MSc Graduate Fellowship – Syndromic Surveillance of Rift Valley Fever in Northern Kenya at International Livestock Research Institute (ILRI)

• The student will implement a project on syndromic surveillance of RVF in livestock. S/he will work with a group of pastoralists to investigate the occurrence patterns and causes of periodic abortions  in livestock. Utilising participatory epidemiology, the student will  detect and map these events, while also collecting  standard epidemiological data and appropriate samples for laboratory investigation of infectious agents that cause these events. During fieldwork, the student will use the available rapid tests for preliminary screening of the collected blood and serum samples. Subsequently, additional laboratory analyses of the samples will be conducted at ILRI Nairobi for confirmatory diagnosis. At the end of the study, the student will analyse the sensitivity and specificity of the diagnostic tests used in the field in the detection of RVF infections in livestock.

Key responsibilities:

The MSc fellow to be recruited into the project will:

• Develop an MSc research proposal in line with the admission requirements of the university.
• Develop a protocol for collecting biological samples required for diagnosis of the causes of abortion in livestock.
• Process the samples mentioned above for a preliminary analysis of the samples using rapid test.
• Process the samples collected for storage and transportation to our laboratories in ILRI Nairobi for confirmatory diagosis.
• Collect epidemiological data that can be used to analyse the incidence and spatial distribution of abortion cases in livestock.
• Analyze the obtained results and prepare a thesis and at least one journal publication.

Requirements:

The ideal candidate should:

• Have registered in a recognized university and is currently pursuing an MSc in either One Health, veterinary epidemiology, animal health, molecular biology or related field.
• Have completed their course work and is ready to begin the research component of their study.
• Possess working experience in working in the field, especially in pastoral production systems.
• Possess working knowledge of MS Office applications.
• Demonstrate good understanding of data handling techniques, analysis, especially involving use of statistical packages such as STATA, R or Python.
• Demonstrate excellent written and verbal communication skills in English.
• Ability to work as part of a team.