Associate Manager – Remote Sensing and Crop Modelling
ICRISAT seeks applications from motivated and dynamic Indian nationals for the position of Associate Manager – Remote Sensing and Crop Modelling to be based at ICRISAT's headquarters in Patancheru, Hyderabad, India. This role is critical to advancing the organization’s mission of improving agricultural productivity and sustainability in semi-arid regions across Asia and sub-Saharan Africa through advanced remote sensing applications in agriculture.
ICRISAT is a non-profit, non-political organization that conducts agricultural research for development in Asia and sub-Saharan Africa with a wide array of partners throughout the world. Covering 6.5 million square kilometers of land in 55 countries, the semi- arid or dryland tropics has over 2 billion people and 644 million of these are the poorest of the poor. ICRISAT and its partners help empower these disadvantaged populations to overcome poverty, hunger and a degraded environment through better agricultural production systems.
ICRISAT is headquartered at Patancheru near Hyderabad, India, with two regional hubs and eight country offices in sub-Saharan Africa. ICRISAT envisions a prosperous, food-secure and resilient dryland tropics. Its mission is to reduce poverty, hunger, malnutrition and environmental degradation in the dryland tropics. ICRISAT conducts research on its mandate crops of chickpea, pigeonpea, groundnut, sorghum, pearl millet and finger millet in the arid and semi-arid tropics. The Institute focuses its work on the drylands and in protecting the environment. Tropical dryland areas are usually seen as resource-poor and perennially beset by shocks such as drought, thereby trapping dryland communities in poverty and hunger and making them dependent on external aid. Please visit - www.icrisat.org
Geospatial Sciences and Big Data (GSBD) at ICRISAT: The GSBD team conducts cutting-edge research on monitoring croplands, natural resources, and geospatial analysis with a focus on ICRISAT’s mandate crops (sorghum, pearl millet, groundnut, chickpea, pigeon pea). The team supports multi-disciplinary efforts to understand regional cropping patterns, changes, and disseminates technologies aimed at improving dryland agriculture.
Responsibilities:
Develop and implement methodologies for crop acreage estimation and crop type mapping using advanced remote sensing techniques.
Conduct yield forecasting for ICRISAT mandate crops in Asia and Africa by integrating satellite data, field observations, and crop models.
Monitor and assess crop health, stress, and growth stages using multi-temporal and multi-spectral satellite data.
Collaborate with interdisciplinary teams to analyse cropping patterns, land use changes, and agricultural trends at regional and national scales.
Process and analyse large datasets from cloud-based platforms (e.g., Google Earth Engine, Sentinel Hub) for agricultural applications.
Support ground truthing and field survey campaigns to validate remote sensing analyses and improve model accuracy.
Maintain and update geospatial databases of crop, soil, climate, and management data for agricultural monitoring and modelling.
Contribute to the development of scalable tools and decision support systems for agricultural stakeholders.
Publish research findings in peer-reviewed journals and present results at international conferences.
Essential Qualifications:
Master’s in Agronomy and Geospatial Sciences, Environmental Modelling, Agriculture or a related field with a focus on remote sensing of agriculture.
Demonstrated experience of atleast 8 years in crop acreage estimation, crop type mapping, and yield forecasting using remote sensing techniques.
Proficiency in handling multi-temporal and multi-spectral satellite data (optical, microwave, hyperspectral).
Strong expertise in using remote sensing software (e.g., ENVI, ERDAS, SNAP, Google Earth Engine) and GIS platforms (e.g., ESRI ArcGIS, QGIS).
Proven ability to publish research outcomes in international journals and contribute to technical reports.
Strong programming skills in R, Python, MATLAB, or similar tools for data analysis and automation.
Experience in field survey design and ground data collection for remote sensing validation.
Excellent written and spoken English, demonstrated through published research articles and technical reports.
Desirable Qualifications:
Experience in data assimilation from diverse sources (e.g., climate, soil, satellite, and socio-economic data).
Familiarity with crop modelling packages such as APSIM, DSSAT, or empirical/semi-empirical models for yield estimation.
Knowledge of advanced statistical analysis, including machine learning and artificial intelligence techniques for agricultural applications.
Understanding of agricultural systems and the interplay between climate, soil, and management practices.
Experience in developing decision support systems or tools for agricultural stakeholders.
Skills in big data analytics and cloud computing platforms (e.g., AWS, Microsoft Azure).
Demonstrated innovation in estimating crop acreage, mapping crop types, and developing scalable solutions for agricultural monitoring.
Strong analytical and logical thinking abilities, with a proactive approach to problem-solving.
General:
This is a contractual role for a period of 36 months (3 years), renewable based on the performance funding availability and the institute’s continuing need for the position.
How to apply:
The position will remain open until a suitable candidate is identified. Shortlisting will start from 16 July 2025. All Applicants should apply with their latest Resume, and the names and contact information of three references that are knowledgeable about their professional qualifications and work experience. All applications will be acknowledged; however, only short-listed candidates will be contacted.
ICRISAT is an equal opportunity employer and is committed to increasing diversity and maintaining a progressive and inclusive workplace. We welcome applications from all qualified candidates regardless of their ethnicity, race, gender, religious beliefs, sexual orientation, age, marital status or whether they have a disability.