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Postdoctoral Fellow, International Centre for Research in Agroforestry, Kenya

Job Description: The World Agroforestry Centre (also known as the International Centre for Research in Agroforestry or ICRAF) is an independent research institution which generates science-based knowledge about the complex role trees play in agricultural landscapes and rural livelihoods. As part of the Centre’s work to bring tree-based solutions to bear on poverty and environmental problems, researchers – working in close collaboration with partners – are developing new technologies, tools and policy recommendations for increased food security and ecosystem health.
The Centre’s headquarters are located in Nairobi, Kenya, and research is conducted in 23 countries in Africa, Asia and Latin America. We are supported by the Consultative Group on International Agricultural Research (CGIAR) and receive funding from over 50 different donors.
To learn more about our organization, please visit our website: www.worldagroforestry.org
The post doc will participate in the multi-centre Global Futures project which is coordinated by IFPRI. The post doc will work closely with post docs at ILRI and CIMMYT who will also be based in Nairobi. The ICRAF post doc will focus on enhancing modelling capability and empirical data to be able to assess the likely economic impacts of agroforestry and other natural resource management interventions. The role includes the following responsibilities:
• Develop methods for improving CGIAR modelling capability in agroforestry and other natural resource management intervention areas. This may involve the direct enhancement of global models like IMPACT or the enhancement of other models that could be linked up (e.g. DSSAT).
• Build up relevant global databases with which to undertake ex ante impact assessments for agroforestry and natural resource management interventions.
• Collaborate with other ICRAF staff to identify priority ex ante impact assessments and to identify key model parameters, such as likely adoption trajectories and productivity, equity, income, and environmental service impacts.
• Support increased use of ex ante impact assessment tools within ICRAF.
• As with all scientists, generate and disseminate scientific publications
• PHD in natural resources or environmental, agricultural, or development economics preferred
• Work experience in modeling is an added an advantage
• Experience in modelling of large scale or multi-country economic or natural resource management systems.
• Use of GAMS programming and familiarity with important models used in the Global Futures project – IMPACT, DREAM, DSSAT
• Excellent data management skills and attention to detail
• Good communication skills – writing, speaking, listening, discussing
• Ability to work in a developing country and in a multicultural environment.
• Proficiency in multiple languages is desirable, fluency in English is necessary
Terms of offer: The World Agroforestry Centre is an equal opportunity employer and offers a collegial and gender-sensitive working environment. We believe that staff diversity promotes excellence and strongly encourage applications from qualified women. This position is on International terms and will be for an initial period of two (2) years, renewable subject to nine (9) months’ probation period, assessment of performance, continued relevance of the position and availability of resources.
How to apply
Applications for the position must include:
• A cover letter illustrating your suitability for the position against the listed requirements and salary expectations
• A detailed curriculum vitae
• The names and addresses of three referees, including telephone, fax numbers and email addresses.
All correspondence should be addressed to the Human Resources Unit, World Agroforestry Centre (ICRAF), PO Box 30677, Nairobi, Kenya OR via email: [email protected] and should indicate “Application for a Post Doctoral Fellow” on their application letters and email submissions.
Applications will be considered until 15th August 2010 or until a suitable candidate is identified and selected.

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