Job Opening ID 475
Number of Positions 1
Duty station Remote
Job Category Internationally Recruited Staff
Terms of offer
This is a Post-Doc appointment on Global Contract terms. CIFOR- ICRAF offers competitive remuneration in commensurate with skills and experience.
This is a remote position.
- Develop and maintain spectral prediction models for a range of soil properties using R statistics and/or Python based on the ICRAF global spectral database. Explore machine learning models, including deep learning for prediction of soil properties. This also includes applying advanced statistical methods and work with large, spectral data sets, collected using the Land Degradation Surveillance Framework and other key methodologies. Apply analytical rigor and applicability of statistical methods used.
- Contribute to the global community on soil spectroscopy by publishing in high impact scientific journals and participating in global soil spectroscopy networks.
- Upload and maintain ICRAF’s spectral databases, including conducting quality control of the spectra and outlier detection and developing scripts to process and analyze soil spectroscopy data.
- Contribute to capacity development efforts across the global network of spectral labs, including conducting trainings and developing training materials on spectral data analysis and predictions. Contribute to the development of online resources such as a web prediction service.
- PhD in Soil Science, Agriculture, Environment, Statistics, Bioinformatics or related field.
- Up to 3 years’ experience in development of analytical tools.
- Experience in working with near-infrared and/or mid-infrared spectra.
- Experience in soil spectroscopy a plus.
- Advanced experience with R or Python.
The main purpose of this position is to contribute to the advancement of methods for processing and analyzing soil spectroscopy data and its application to soil health monitoring and carbon accounting.
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