The Alliance of Bioversity International (www.bioversityinternational.org) and the International Center for Tropical Agriculture (CIAT) (www.ciat.cgiar.org) delivers research-based solutions that harness agricultural biodiversity and sustainably transform food systems to improve people’s lives. Alliance solutions address the global crises of malnutrition, climate change, biodiversity loss, and environmental degradation.With novel partnerships, the Alliance generates evidence and mainstreams innovations to transform food systems and landscapes so that they sustain the planet, drive prosperity, and nourish people in a climate crisis.
The Alliance is part of CGIAR, a global research partnership for a food-secure future.
The Alliance is currently searching for a motivated and high performing Postdoctoral Researcher, specializing on climate and environmental data science, to support development of innovative and high-quality analytical solutions to help understand climate impacts, crop and location-specific risks and adaptation options, and inform relevant investments in sustainable agriculture and climate adaptation. The incumbent will contribute to developing analytical and modelling frameworks that integrate biophysical, ecological, and socio-economic domains to evaluate the impacts of various adaptation interventions, considering future drivers of change, such as climate change and economic growth. The Postdoctoral Researcher will design and implement model-based analyses will follow robust conceptual/theoretical frameworks based on recent literature and the IPCC Sixth Assessment Report and will be fully automated using software code (in R and/or Python), documented adequately to ensure replicability. The incumbent therefore will invest time in designing the analytical pipelines and identifying ways to store software code (through version control systems, R packages) and to document these analytical routines for use by others.
In collaboration with partners of the One CGIAR Initiative on “Informing Sustainable Development pathway with Foresight and Data” design of climate data cube structure and data models to support integration of climate variability data. Leverage expertise from the Alliance and CGIAR on data architecture to design and automate ETL (Extract, Transform, Load) processes for the climate data cube that facilitates modeling.
Perform, automate and document analysis of climate data trends and population of climate data cube(s).
Development of geospatial data and models and resultant datasets to support incorporation of key themes (e.g., Biodiversity, farming systems) into other foresight analyses.
Work closely with project partners and other teams in the Alliance to design and perform data analysis for agroclimatic advisory design and deployment, climate risk assessment, through the operationalization of innovative methodologies that take consideration of partners’ and local stakeholder needs.
Contribution to quality assurance and quality control of climate and other related datasets used throughout the project cycle.
Produce scientific papers for peer-reviewed journals and proceedings.