Research Associate (Crop Experiments & Sensing)

About the role

The School of Materials Science and Engineering (MSE) at NTU is looking for a Research Associate to join an interdisciplinary project funded by the National Research Foundation Singapore (NRF) under its AI-for-Science Catalytic Grant. The project develops AI-driven urban farming systems for crop yield and trait optimisation. The researcher works in a multidisciplinary team, with main responsibilities in greenhouse operations, crop experimentation and plant proximal/remote sensing.

Key responsibilities

• Coordinate and monitor the execution of crop experiments, ensuring technical and manpower requirements are met.
• Oversee remote sensing systems (RGB, 3D, hyperspectral and thermal imaging) for crop monitoring.
• Assist in deploying, operating and maintaining proximal sensing systems for controlled environment agriculture, including RGB, 3D, hyperspectral and thermal cameras and agritech sensors.
• Procure experimental equipment, sensors and peripherals.
• Maintain data pipelines for greenhouse and CEA experiments, adapting source code to different crops (e.g. camera height calibration, image segmentation).
• Consolidate data from multiple sources for machine learning modelling, including continuous interventions, plant sensing, ground-truth yield and mineral content data and metadata, and maintain databases with backups.
• Troubleshoot sensing issues with vendors and monitor active experiments with phenotyping software, including dynamic irrigation scheduling.
• Coordinate greenhouse operations with the greenhouse manager, including manpower planning, seedling production, fertigation tank refilling and hardware support.
• Prepare technical progress reports and respond to information requests from funding agencies.

Required profile

• Master's degree in Remote Sensing, Agricultural/Electronic or Biosystems Engineering, Plant or Computer Science, Agronomy or a related field.
• At least 2 years of relevant experience; experience in plant/crop experiments and phenotyping is an advantage.
• Willingness to work with agritech IoT equipment.
• Ability to manage competing priorities, projects and deadlines, and to work independently with minimal supervision.

Required skills

• Advanced knowledge of proximal/remote sensing and cameras.
• Advanced knowledge of image processing and programming.
• Excellent communication skills and teamwork in an international, interdisciplinary setting.