As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets that are relevant to industry demands while working on research projects in SIT.
The primary responsibility of this role is to deliver an industry-focused research and development project on Electrical Equipment Health Monitoring (EEHM) for a marine vessel power and propulsion systems. You will be part of a multidisciplinary research team to develop advanced predictive maintenance solutions involving sensor integration, high-speed data acquisition, electrical and vibration signal analysis, anomaly detection, and health analytics for marine electrical equipment.
The role will involve prototype development, laboratory validation, onboard system integration, operational trials, and data-driven fault detection for naval applications, with the objective of improving equipment reliability, operational readiness, and maintenance effectiveness in marine environments.
Key Responsibilities:
As a Research Engineer (Electrical Equipment Health Monitoring - Marine electrical systems), you will be part of a multidisciplinary research team working on advanced predictive maintenance technologies for marine electrical systems. You will:
- Participate in and manage the research project with the Principal Investigator (PI), co-investigators, and industry partners to ensure all project deliverables and milestones are met.
- Design, develop, and integrate Electrical Equipment Health Monitoring (EEHM) prototypes for marine Power Generation Systems and Thruster Systems.
- Develop and implement high-speed data acquisition (DAQ) systems for voltage, current, temperature, and vibration monitoring.
- Design experiments and conduct laboratory validation for electrical and mechanical fault detection under normal and induced fault conditions.
- Develop and implement condition monitoring, anomaly detection, and fault prediction algorithms for rotating electrical equipment.
- Analyze electrical, thermal, and vibration signatures for early detection of bearing faults, winding faults, imbalance, and other equipment anomalies.
- Develop data analytics pipelines, machine learning models, and visualization dashboards for predictive maintenance applications.
- Support HMI/dashboard development for real-time monitoring, trend analysis, alarm management, and data visualization.
- Conduct sensor calibration, signal validation, and system performance evaluation to ensure data integrity and monitoring accuracy.
- Support onboard integration, commissioning, and operational validation of EEHM prototypes onboard vessels.
- Troubleshoot hardware/software integration issues and optimize system reliability in marine operational environments.
- Prepare technical reports, system documentation, calibration records, and project updates for stakeholders and sponsors.
- Support knowledge transfer, prototype development, technology demonstration, and system deployment activities.
- Carry out Risk Assessment and ensure compliance with Workplace Safety and Health (WSH) regulations and marine operational requirements.
- Coordinate procurement activities and liaise with vendors/suppliers for sensors, DAQ hardware, embedded systems, and testing equipment.
- Work independently, as well as within a multidisciplinary team, to drive research, development, testing, and deployment activities.
Job Requirements:
- Degree/Master's in Electrical Engineering, Electronics Engineering, or related fields.
- Strong knowledge of condition monitoring, predictive maintenance, signal processing, and electrical machine diagnostics.
- Experience in data acquisition systems, industrial instrumentation, and high-frequency sensor integration.
- Experience in electrical and vibration data analysis for rotating machinery and fault diagnostics.
- Experience in designing and developing experiments and associated test setups for monitoring and troubleshooting electrical systems.
- Proficiency in MATLAB, Python, LabVIEW, or similar tools for data analytics and visualization.
- Experience in machine learning, anomaly detection, or predictive analytics for industrial applications is an advantage.
- Knowledge of vibration analysis, thermal monitoring, and power quality assessment is preferred.
- Experience in embedded systems, edge computing, or industrial communication protocols is advantageous.
- Knowledge of marine electrical systems, shipboard integration, or industrial automation systems is an advantage.
- Strong problem-solving, analytical, and technical documentation skills.
- Passion for applied research, prototype development, and industry collaboration.
Key Competencies
- Strong analytical and troubleshooting skills.
- Ability to work in a team-oriented and interdisciplinary environment.
- Effective communication and technical documentation skills.
- Adaptability to work on industry-focused projects with tight deadlines.
- Able to build and maintain strong working relationships with people within and external to the university.
- Possess strong analytical and critical thinking skills
- Show strong initiative and take ownership of work
