Reference number: 2488
Job status: In-progress
Job category: Local Position
Duty station: Bogor, Indonesia
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CIFOR-ICRAF
The Center for International Forestry Research (CIFOR) and World Agroforestry (ICRAF) envision a more equitable world where trees in all landscapes, from drylands to the humid tropics, enhance the environment and well-being for all. CIFOR and ICRAF are non-profit science institutions that build and apply evidence to today’s most pressing challenges, including energy insecurity and the climate and biodiversity crises. Over a combined total of 65 years, we have built vast knowledge on forests and trees outside of forests in agricultural landscapes (agroforestry). Using a multidisciplinary approach, we seek to improve lives and to protect and restore ecosystems. Our work focuses on innovative research, partnering for impact, and engaging with stakeholders on policies and practices to benefit people and the planet. Founded in 1993 and 1978, CIFOR and ICRAF are members of CGIAR, a global research partnership for a food secure future dedicated to reducing poverty, enhancing food and nutrition security, and improving natural resources.
CIFOR-ICRAF is looking for a
Remote Sensing Assistant
Overview
The remote sensing assistant's primary responsibility is to support the production of high-quality, replicable, and scalable land use/cover products using desktop and cloud-based remote sensing platforms. The assistant will also contribute to adapting and extending features within the current codebase and workflow; this includes developing, testing, and documenting associated algorithms. Collaborating closely with the Remote Sensing and GIS team and scientists from various fields, the assistant will help deliver high-quality land cover maps with transparent accuracy assessments.
Duties and responsibilities
1. Data Acquisition and Preparation
- Select, collect, compile, and pre-process high-quality, time-series satellite imagery from reliable sources using desktop or cloud-based remote sensing engines.
- Support the development of rulesets/interpretation keys and image interpretation procedures for classifying land use/cover types in Indonesia using satellite imagery.
2. Data Quality Assurance and Analysis
- Assist in performing replicable accuracy assessments and refining land use/cover data.
- Solicit and incorporate feedback from internal and external colleagues to improve land use/cover classification accuracy.
- Assist in conducting land use/cover change analysis and other related LULC analytical tasks as required.
- Contribute to the development of case studies on the application of land use/cover maps.
3. Field Survey Planning, data management and documentation
- Assist in planning field surveys and organising the collected data for model training, validation, and accuracy assessment.
- Contribute to documenting all technical procedures for image classification, including code annotation, within version-controlled notebooks.
- Assist in organising spatial datasets into a database system.
Education, knowledge and experience
A bachelor’s degree in a relevant Science, Technology, Engineering, or Mathematics (STEM) field, including but not limited to Geomatics Engineering, Computer Engineering, Earth Sciences.
• A thesis or final project utilising desktop or cloud-based remote sensing platforms is a plus. Course completions related to cloud-based remote sensing platforms (e.g., Google Earth Engine) are highly valued.
• Two years of experience supporting remote sensing projects using cloud-based platforms is preferred. However, recent graduates with experience using cloud-based remote sensing platforms during their BSc are encouraged to apply.
• Proficient in written and spoken English is essential.
• A strong understanding of remote sensing principles and their practical application is required, encompassing knowledge of various sensors, pre-processing methods, data fusion techniques, hierarchical classification, Object-Based Image Analysis (OBIA), and accuracy assessment methodologies.
• Hands-on expertise assisting with projects using Google Earth Engine (GEE) or similar platforms. Specific examples of contributions to land cover mapping, land-use change monitoring, or other relevant applications are highly beneficial.
• Demonstrated ability to effectively manage and process remote sensing datasets within desktop environments (e.g., eCognition, ENVI, ERDAS Imagine) and cloud platforms (e.g., Google Earth Engine, Microsoft Planetary Computer), including a strong understanding of data structures, formats, and pre-processing techniques.
• Experience in programming and scripting languages commonly used within Google Earth Engine, such as JavaScript and Python, is preferred.
• Proficiency in using version control systems (e.g., Git) is highly desirable. Evidence of past contributions to shared repositories like GitHub or GitLab would be a significant asset.
Terms and conditions
This is a Temporary Staff position. CIFOR-ICRAF offers competitive remuneration in local currency, commensurate with skills and experience.
• The appointment will be for 6 (six) months with the possibility of extension contingent upon performance, continued relevance of the position and available resources.
• The duty station will be in Bogor, Indonesia.
To apply, please visit our career site at: https://www.cifor-icraf.org/about/work-with-us/
To learn more about CIFOR-ICRAF, please visit our websites at: https://www.cifor-icraf.org
CIFOR-ICRAF promotes Gender Diversity – Applications from women professionals are encouraged.
CIFOR-ICRAF is an equal opportunity employer. It fosters a multicultural work environment that values gender equality, teamwork, and respect for diversity.
Application process
The application deadline is 30 May 2025
We will acknowledge all applications, but will contact only short-listed candidates.
