Rolls-Royce@NTU Corporate Lab is looking for a Research Associate to work in our project on Artificial Intelligence for smart discovery, a sub-project under Data Analytics and Complex Systems. The project aims to provide data analytics users (e.g. data scientists, subject matter experts, laymen, etc..) with tools and processes to examine large datasets and overcome tedious and time-consuming processes such as: Signal enhancement, feature generation and visualization; Knowledge representation and real time analysis.
This project will have the following key deliverables:
- Baseline prototype development for feature engineering
- Enhancement on baseline system for smart discovery
- Demonstration of final prototype of knowledge discovery and layman analytics capability
- Development of novel algorithms and IPs related to the project scope
- Conduct in-depth research on time-series data to examine various features associated with rare events detection, automatic identification of important parameters, weak signal detection and enhancement and unsupervised clustering of time series data
- Prototype development for feature engineering and enhancement on baseline systems for smart discovery
- Explore novel machine learning based algorithms to automate and speed up feature engineering for time series data
- A good Master degree holder with sufficient research experience in one of the following areas: Data Analytics, Machine Learning, AI or related fields
- Good experiences in one or more of the following areas: time series data analysis, signal enhancement and feature extraction, auto feature engineering tools, big data processing, machine learning algorithms, neural networks
- Excellent programming skills in PYTHON, R, MATLAB, C/C++, etc.
- Excellent analytical, technical and problem-solving skills
- Good publication record in reputable journals and/or conferences
- A team player with good people skills, innovative, resourceful and self-motivated.
- Strong verbal and written communication skills.
The successful candidate will receive a competitive remuneration package commensurate with their qualifications and experience.
Please note that only successful candidates would be notified.