Post-Doctoral Scientist- Evidence Synthesis at International Livestock Research Institute (ILRI)

About the position

The role aims to generate robust, actionable evidence, translate it into compelling outputs for policy, investment and practice, and strengthen ILRI’s capacity in evidence-synthesis methodologies and data-driven decision-making. The position will focus particularly on climate change impacts on livestock and overall agrifood systems. This position will be a part of ILRI’s Livestock, Climate and Environment (LCE) Program.

Key Responsibilities

Research & Evidence Synthesis

• Design, conduct and oversee evidence syntheses (evidence gap maps, scoping reviews systematic reviews, meta-analyses,) on topics relevant to livestock systems, food systems, climate change, environmental or health impacts.
• Formulate research questions, develop protocols (e.g., adhering to PRISMA / ROSES/ other industry standards), carry out systematic literature searches, screen and extract data, assess risk of bias and methodological quality, synthesise results and interpret findings for stakeholders.
• Adapt or develop advanced synthesis methods (e.g., network meta-analysis, mixed methods synthesis, AI-assisted screening, living review frameworks) as relevant to complex interventions in agriculture, livestock/food systems.
• Contribute to or lead the development of new synthesis tools, workflows or software packages to increase efficiency and rigour of evidence synthesis.

Publication and Dissemination

• Lead the writing of high-impact journal manuscripts (first or co-first author) from synthesis projects and present findings at international conferences, workshops and stakeholder fora.
• Develop and disseminate research outputs beyond journals: policy briefs, research briefs, stakeholder summaries, infographics, data-visualisations, webinars.
• Work with ILRI’s communications, outreach and knowledge-management teams to ensure effective translation of evidence for non-academic audiences.

Collaboration, Project Management & Capacity-Building

• Collaborate with multidisciplinary teams across ILRI’s programmes, and with external academic, policy and development partners.
• Manage synthesis projects: timelines, budgets, deliverables, data management, quality assurance and reporting.
• Mentor and train ILRI and CGIAR scientists, junior researchers and staff in evidence-synthesis methodologies, screening tools (e.g., Covidence, Rayyan, EPPI-Reviewer, SysRev, PROSPERO), meta-analysis software (e.g., RevMan, R, STATA), and best practices in systematic reviewing.
• Substantially contribute to identifying funding opportunities, preparing grant proposals and building partnerships to sustain future evidence-synthesis work.

Professional Development & Strategic Engagement

• Engage in relevant professional development: workshops, networks, methods training to deepen skills in evidence-synthesis innovation and research translation.
• Stay abreast of emerging methodologies, technologies (e.g., machine-learning assisted screening, natural-language-processing in reviews) and global trends in evidence synthesis, food systems research and livestock development.
• Contribute to institutional strategy on evidence-synthesis, data-driven communication and impact-oriented research uptake.

Requirements

• PhD in economics, epidemiology, public health, social sciences, agriculture, veterinary science, food systems with deep expertise in evidence-synthesis methodology or a related field.
• Demonstrated prior experience leading or substantially contributing to systematic reviews, meta-analyses (or scoping reviews, evidence gap maps), especially in the development domain (agri-food systems, livestock, public health, gender, environment).
• Strong publication record (ideally at least two first-author peer-reviewed publications on systematic reviews or meta-analysis) and familiarity with academic publishing processes.
• Proficiency in statistical analysis software and languages (e.g., R, STATA, SPSS, Python) including systematic review and meta-analysis packages and scripting.