Research Scientist (Field-level Agricultural Digital Twin)

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 build the program’s field-level crop digital twin under Thrust 2 (Developing Digital Twins). The successful candidate will couple a 4Dplant structure model with the ecosys process model through knowledge-guided AI, continuously integrating sensor and satellite observations to constrain model states and parameters, and apply the digital twin to rice and/or agroforestry systems in Southeast Asia.

Key Responsibilities:

• Lead research on process-based modelling and knowledge-guided AI for field-level digital twins.
• Couple a 4D plant structure model with the ecosys biogeochemical process model through knowledge-guided AI.

• Integrate field and sensor data into the digital twin through model-data fusion and data assimilation.
• Apply the digital twin to rice and/or agroforestry systems, quantifying model uncertainty.

• Develop and maintain model code (e.g. Python, Fortran)and run simulations on HPC.
• 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 ecology, agricultural/environmental science, Earth system science, computer science or a related field.
• Extensive experience combining process-based ecosystem or crop modelling with AI, such as model-data fusion, data assimilation or physics-constrained deep learning.

• Strong programming skills in Python and PyTorch.
• Excellent communication and scientific writing skills in English, the working language of the US–Singapore team, publications and reports.

Preferred:

• Experience with 3D plant structure modelling.
• Experience with Fortran-based process models such as ecosys.

• Experience with uncertainty quantification and high-performance computing.
• Familiarity with rice or agroforestry systems.

• 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:

_Interested candidates should submit their resume/CV together with a cover letter outlining their qualifications and relevant experience for the position to Gabriel Tan (gabriel.tan@iarcs-create.edu.sg)with the subject line “__KGAI4Ag Research Scientist (Field-level Agricultural Digital Twin) – Singapore__”. Please also include the transcripts of undergraduate studies, the names and contact details of three professional referees._

Applications will be considered until the corresponding position has been filled. Only shortlisted candidates will be notified.