Research Scientist (Reinforcement Learning for Decision Support)

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 advance reinforcement learning under Thrust 3(Decision-Making). The successful candidate will build decision-support tools that use agricultural digital twins as simulators, from farm management to regional policy design. The work will identify adaptive management strategies that balance crop productivity, greenhouse gas emissions and economic outcomes, and help translate the program’s digital twins into tools that farmers, agencies and partners can act on.

Key Responsibilities:

• Lead research on reinforcement learning and sequential decision-making under uncertainty.

• Couple RL methods with crop digital twins, using them as simulators to identify adaptive farm management strategies that balance yield, greenhouse gas emissions and farmer income.

• Extend methods to multi-agent and policy settings to support national and regional decisions, including food trade and climate-related scenarios.

• Develop bandit, optimization and uncertainty quantification approaches that make recommendations robust and data-efficient.

• Translate research outputs into decision support systems with the data platform and digital twin teams.

• 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.

Qualifications and Experience:

Required:

• PhD in computer science, machine learning, operations research, applied mathematics, statistics or a related field.

• Extensive experience in reinforcement learning or sequential decision-making, shown by publications in leading machine learning venues.

• 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 multi-agent systems, bandit algorithms or simulation-based optimization.

• Experience with uncertainty quantification and decision-making under uncertainty.

• Experience working with physics-based simulators, digital twins or decision support systems.

• Familiarity with agriculture, environmental science or sustainability applications.

• 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 (Reinforcement Learning for Decision Support) – 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.