📢 Research Opportunity | AI/ML × Climate-Resilient Livestock Production

Responsibilities
The selected candidates will work on developing AI/ML-based predictive models for early detection of heat and drought stress and prediction of productivity losses in sheep and goats using real-time sensor, physiological, behavioural and environmental data. The work will also involve time-series analysis, feature engineering, model validation, Explainable AI (XAI) and development of an integrated Climate Resilience Index (CRI) for identifying and ranking climate-resilient animals. The ultimate goal is to contribute to an AI-enabled early-warning and decision-support system for climate-resilient livestock production.
Qualifications
Postgraduate qualification in AI/ML, Computer Science, Data Science, Statistics, Bioinformatics, Computational Biology, Engineering or related disciplines, with strong programming skills in Python/R and practical knowledge of machine learning, deep learning, statistical modelling and data analytics. Experience with sensor/IoT data, time-series analysis, predictive modelling, PCA/multivariate analysis, Scikit-learn, TensorFlow/PyTorch or similar platforms will be highly desirable. Background or interest in livestock, agriculture, climate science or biological sciences will be an added advantage.
Candidates with strong AI/ML expertise who are interested in applying data-driven technologies to climate-resilient livestock production are particularly encouraged to connect.

Work arrangement
No