Scientist I

About the Position:

This role will be hosted by the International Water Management Institute (IWMI) and based at the IWMI headquarters in Rome, Italy.

The Scientist I, Remote Sensing for Climate Finance will assess investments from climate finance mechanisms in agriculture on its impacts on sustainable water resources management.

This will be achieved by utilizing a combination of remote sensing datasets, field measurements, and modelling tools to derive assessment-specific Key Performance Indicators (KPIs) for water resources.

Furthermore, for crop and water productivity-based indicators, the incumbent will use remote sensing modelling tools currently in operation in IWMI in combination with new data-driven approaches and will collaborate with the CGIAR sustainable finance team to coordinate the entire investment assessment cycle.

Responsibilities:

Undertake a literature review to explicitly develop investment-specific KPIs cross-cutting water and climate to assess investments in water, land, energy and food systems on climate bankability, its relevance to national sustainable strategies, and investor's climate goal.

Applying earth observation-based models to derive productivity (land and water) indicators at different spatial scales across multiple cropping systems for both pre-investment and post-investment portfolio assessment.

Conduct high-quality research on the role of climate finance in enhancing sustainable water resource management.

Analyze the effectiveness of various climate finance mechanisms in supporting water projects, including public-private partnerships, green bonds, carbon credits and blended finance.

Develop case studies and policy briefs highlighting successful models and best practices.

Collaborate with a multidisciplinary team to develop, integrate, and implement innovative approaches for mainstreaming water in the climate finance portfolio in the regions where IWMI operates.

Collaborate with team members to design and implement research projects on climate finance and water.

Contribute to the scientific advancement and methodological developments of IWMI's digital water innovation toolsets.

Develop technical guidance and training materials for custom geospatial applications.

Prepare high-quality research reports and journal articles.

Provide technical support to researchers for complex geospatial analysis in various research and management projects at IWMI headquarters.

Assist in training and capacity-building activities related to the tools developed within the Water Productivity/Water Accounting group.

Requirements:

PhD in Water Resources Management, Agricultural Science, Environmental Science, hydro-informatics or a related discipline.

At least three years of demonstrated experience in conducting interdisciplinary research, preferably at the intersection of climate and water resources, using earth observation data and modeling tools.

Evidence of scientific publishing, demonstrated by a very good publication record in peer review journals (minimum of 5 articles).

Experience in calculations of water footprint measures across the value chain preferably in the Global South.

Experience in use of soil sensors data/validation/ground-truthing.

Prior experience in using supervised and unsupervised algorithms, including machine learning methods on large spatial datasets in Python, R, or any other programming language.

Experience in using Amazon Web Services, Google Earth Engine or other cloud-based earth observation data processing environments for geospatial tool developments.

Experience designing and implementing approaches for data-scarce environments.

Strong understanding of deriving biophysical indicators on different types of crop systems from remote sensing and model-based approaches. Strong data assimilation and image fusion skills to integrate existing and upcoming satellite datasets and their processing methods for crop water use mapping.

Strong understanding of impact assessment frameworks using earth observation data especially when dealing with small land sizes (

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