Duties

The appointee will be responsible (a) develop, train, and test AI/Machine Learning models for anomaly detection and predictive analytics using sensor data; (b) assist in processing, cleaning, and managing time-series data streams from IoT sensors (e.g., accelerometers, strain gauges, tilt sensors); (c) support the configuration, calibration, and data acquisition setup for IoT monitoring hardware; (d) collaborate with the research team to validate AI model insights against real-world engineering constraints; and (e) assist in preparing technical reports, progress updates.

Appointment Criteria

Applicants should have (i) a Bachelor's or Master's degree (or currently enrolled in a postgraduate program) in Engineering (e.g., Civil, Mechanical, Electronic, Systems, or Biomedical Engineering with a strong structural/mechatronics focus); (ii) strong programming skills in Python or MATLAB (experience with libraries like NumPy, Pandas, TensorFlow, or PyTorch is highly preferred); (iii) solid understanding of Machine Learning, Deep Learning, or statistical signal processing; (iv) ability to interpret data related to structural mechanics, vibrations, or kinematics; (v) experience working with IoT hardware, microcontrollers (e.g., Arduino, Raspberry Pi), or edge computing, (vi) strong problem-solving abilities and a self-driven attitude toward research; and (vii) good written and verbal communication skills.

Application Deadline

Until the Position is Filled