Postdoctoral Fellow - Agricultural Water Management Analytics
The International Water Management Institute (IWMI) is looking for a Postdoctoral Fellow who will lead research on developing new analytical solutions (using machine learning tools) to assess the impacts of agriculture management (AWM) technologies for smallholder farmers on water productivity, water abstraction/use and agriculture production. The fellow will lead scientific outreach and project management activities in relevant projects. Working closely with the hydro-informatics group at IWMI, the Fellow will contribute towards ongoing activities in developing innovation solutions for agriculture water management (AWM) assessments.
DUTIES AND RESPONSIBILITIES:
- Conduct innovative research on assessing rain-fed and irrigated innovations to ensure food security at farm level.
- Develop new algorithms to assess on-farm water management practices in agriculture. .
- Develop a coordinated approach using machine learning to assess the utilization of surface water and groundwater resources at household level for agricultural production and multi-purpose use in a sustainable manner.
- Develop a systems approach to assess the impacts of innovative AWM solutions on water and agricultural productivity in farming systems.
- Prepare research reports and journal articles for publication, in addition to conference/seminar papers.
- Synthesize and communicate high-quality research findings in the East Africa region and in the wider research and development community.
EDUCATIONAL QUALIFICATIONS AND EXPERIENCE:
- A PhD (or equivalent) in the field of hydro-informatics, agronomy, agricultural or irrigation engineering, agricultural water management, statistics, or a related field.
- Prior experience of using machine learning in the field of on-farm water management and water use.
- Prior experience in developing data platforms, and writing and executing scripts in Python/R or other similar programming languages.
- A good understanding of the soil-water-plant-continuum, farm system assessments, on-farm water management and irrigation techniques is an asset.
- Experience with interdisciplinary research and collaboration in developing countries.
- Experience in conducting research in multidisciplinary, multi-partner projects across several regions or countries.
- Work and networking experience in Africa. Experience in Asia is beneficial.
- Experience with knowledge products, outreach and communications is beneficial.
KNOWLEDGE AND SKILLS:
- A strong record of accomplishment in research relevant in using machine learning and hydro-informatics to develop solutions for the assessment of impacts of on-farm water management on agriculture production.
- Demonstrated success in using descriptive (clustering, PCA), predictive (linear regression neural networks), or prescriptive (optimization) in field of agriculture.
- Demonstrated success in designing and conducting research independently as well as within multidisciplinary teams.
- Proven ability to work collaboratively and effectively within multidisciplinary teams and with academic and non-academic stakeholders.
- Building and maintaining strong external partnerships and alliances in complex institutional environments.
- Strong analytical mind-set.
- Excellent communication skills and the ability to explain complex issues clearly.
- Evidence of intellectual rigor and application of natural sciences in informing policy and investments.
- Record of relevant peer-reviewed outputs.
- Willingness to live, work and travel in developing countries in Asia and Africa.
This Postdoctoral Fellowship offers an annualized stipend of $40,580/year, comprehensive international insurance coverage a transportation allowance and 24 days paid annual leave. If the successful candidate requires international relocation, s/he will be eligible for additional allowances, which include housing, shipping assistance, dependent education contribution, a settling-in allowance and home-leave travel. The duration of the contract be for a two-year period.
IWMI is an equal opportunity employer and emphasizes the importance of gender diversity and inclusiveness in identifying candidates for this position and its staff more generally.