The School of Chemistry, Chemical Engineering and Biotechnology (CCEB) at NTU Singapore, in collaboration with Wageningen University & Research (WUR), is part of the Singapore Indoor Farming System (SingFarm)—a CREATE-NRF programme focused on building a sustainable, data-driven food production model with strong industry relevance. The programme contributes to Singapore’s ambition of achieving 20 per cent local production of its fibre (vegetables, mushrooms, etc.) by 2035. The candidate will work in a multinational team at the forefront of Singapore’s agricultural innovation and food security.

The Research Associate will take on a significant role in developing and applying simulation and machine learning models for Asian leafy vegetables to predict growth, transpiration, resource use, and yield under controlled environments, with a focus on production under higher temperature and humidity. The Research Associate will also build self-learning models using continuous sensor data, calibrate and validate them with experimental datasets, and collaborate with project partners to support predictive climate and crop control strategies for indoor farming in Singapore.

Key Responsibilities:

• Conduct climate room experiments by varying environmental conditions for the growth of pak choi

• Develop, calibrate, and validate an explanatory, dynamic crop growth model for pak choi

• Write scientific papers and participate in international conferences

Job Requirements:

• A Master’s degree in plant science, biology, agronomy, or related fields

• ​ Strong command of written and communication skills

• Knowledge of plant and crop physiology

• Experience or a demonstrated interest in a quantitative approach to crop growth Knowledge or experience in programming is preferred

• Strong presentation skills for both academic and non-academic audiences

• Good collaboration skills and ability to work effectively in a team

We seek a diverse and inclusive workforce and is committed to equality of opportunity. We welcome applications from all and recruit on the basis of merit, regardless of age, race, gender, religion, marital status and family responsibilities, or disability.

We regret that only shortlisted candidates will be notified.