Post Doctoral Fellow – Targeting Climate-Smart Development Interventions under Multiple Uncertainties

Project Summary

Countless ‘climate-smart’ technologies are available to help farmers in Africa adapt to climate change. A wide range of practices has proven successful under certain conditions. However, we know that the success of interventions to improve livelihoods depends on a host of factors, for many of which little information is available and that vary significantly across time and space. Despite knowledge gaps and imperfect  information, decisions about what interventions to promote where are on the agenda of decision-makers in governments, NGOs and international donor organizations daily. Decision makers need appropriate tools for assisting these decisions. Such tools require new approaches that adequately consider uncertainties and are able to capture the unclear nature of relationships between site factors on which success or failure of interventions depends. The incumbent will work with the decision engagement and analytics team at ICRAF and beyond to develop methods for targeting interventions under uncertainty, and for projecting likely impacts of such interventions. This will be achieved using probabilistic modeling, Bayesian networks and other similar approaches that do not rely on purely deterministic models of farmer reality. 

For more details and application Visit ICRAF website

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