Research Scientist (Remote Sensing and Knowledge-Guided AI)

About KGAI4Ag:
Advancing Knowledge-guided AI to Develop Agricultural Digital Twins for Singapore’s Climate Resilience (KGAI4Ag) is a research program of the Illinois Advanced Research Center at Singapore (Illinois ARCS), a research institute funded by the National Research Foundation (NRF) Singapore under the CREATE program.KGAI4Ag sits within the Southeast Asian Innovation Alliance for a Global Model of Future Agri-Food Systems (SIGMA), a U.S.–Singapore academic research alliance co-led by the University of Illinois Urbana-Champaign (UIUC) and the National University of Singapore (NUS) to enhance food security, sustain the environment and build resilient communities across Southeast Asia.

KGAI4Ag is developing first-of-its-kind digital twins for ASEAN agroecosystems by advancing knowledge-guided AI (KGAI), which integrates scientific principles with machine learning. The program is organized around three research thrusts: (1) Characterizing Physical Reality, which combines low-cost IoT field sensors, cameras and satellite remote sensing into analysis-ready datasets; (2)Developing Digital Twins, which couples dynamic 4D plant models with biogeochemical modelling through KGAI-based data assimilation at the field scale, and upscales these to the regional scale through a Bridge Model framework; and (3)Decision-Making, which turns digital twin outputs into AI-driven decision support for farm management, food trade, and measurement, reporting and verification (MRV) of agricultural carbon outcomes. Field work currently focuses on rice systems in Vietnam and cacao agroforestry in Indonesia.

About This Role:
KGAI4Ag seeks a Research Scientist to lead the program’s Earth observation research under Thrust 1 (Characterizing Physical Reality). The successful candidate will develop knowledge-guided AI methods that combine ground and satellite data to map crops, environmental and management variables across Southeast Asia, supporting the project’s crop digital twins. The role works closely with the field-level and regional digital twin teams to ensure that remote sensing products feed directly into model-data fusion and decision support.

Key Responsibilities:

• Lead research on Earth observation and geospatial AI to map crops, environmental conditions and management practices across Southeast Asia.
• Develop knowledge-guided AI, deep learning and computer vision methods for satellite, drone and ground-sensor data.
• Fuse field, IoT sensor and multi-satellite data, including daily geostationary imagery, into consistent, analysis-ready datasets at field to regional scales.
• Integrate remote sensing products with process models to deliver inputs and constraints for the crop digital twins.
• Apply radiative transfer modelling and scalable cloud workflows (e.g. Google Earth Engine) to extend analyses across the region.
• Publish in leading journals and present at conferences and project meetings.
• Collaborate across US–Singapore teams at UIUC, NUS and partner institutions, and mentor students and junior researchers.
• Undertake occasional travel to field sites in Vietnam and Indonesia and to partner institutions in the US.

Qualifications and Experience:
Required:

• PhD in remote sensing, geography, Earth/environmental science, computer science or a related field.
• Extensive experience in satellite remote sensing and machine learning, shown by first-author publications on satellite data analysis or geospatial deep learning.
• Strong programming skills in Python and a deep learning framework such as PyTorch.
• Excellent communication and scientific writing skills in English, the working language of the US–Singapore team, publications and reports.

Preferred:

• Experience with multi-sensor data fusion across optical, geostationary and drone platforms.
• Experience with radiative transfer modelling or physics-informed / knowledge-guided machine learning.
• Proficiency with Google Earth Engine and large-scale geospatial processing on HPC or cloud platforms.
• Familiarity with agricultural systems in Southeast Asia or with crops and agroecosystem modelling.
• Willing to participate in online meetings outside of regular working hours to ensure timely communication and continuity of business, in view of the strategic and affiliated relationship between the Illinois ARCS and the UIUC, as well as the time zone differences between the two locations.

Application Process:
Intere…