Research Assistant

HKCC / SPEED (CPCE)

Duties & Responsibilities

Conduct literature review and technical data collection on AI, machine learning, optimization, and techno-economic analysis for thermal systems.
Develop end-to-end data-driven modeling pipelines including preprocessing, feature selection, training, and performance evaluation.
Assist in creating AI-enabled decision-making frameworks integrating thermodynamic, economic, and sustainability indicators.
Analyze large multi-parameter datasets and develop correlations, surrogate models, prediction tools, and visualizations.
Perform other duties as assigned.

Honours degree in artificial intelligence, computer science, data science, engineering, or related disciplines.
Knowledge and practical experience in AI, machine learning, deep learning, numerical modeling, or computational optimization.
Proficiency in Python and/or MATLAB with experience in TensorFlow, PyTorch, or Scikit-learn.
Experience developing data-driven pipelines with preprocessing, model development, validation, and statistical assessment.
Ability to work independently, manage computational tasks systematically, and complete deliverables on schedule.
Strong sense of responsibility, research enthusiasm, attention to detail, and collaborative skills.