Research Fellow (in AI)

Job Purpose:

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 on an industry innovation research project, Agent-Driven Industry 5.0 Cognitive Control Tower Platform, where you will be part of the research team to develop AI-driven predictive and prescriptive capabilities (e.g., predictive maintenance, OEE optimisation and dynamic scheduling) and an agentic AI decision-support system on SIT's Industry 5.0 testbed, in collaboration with industry partners.
Key Responsibilities:
. Participate in and manage the research project with Principal Investigator (PI), Co-PI and the research team members to ensure all project deliverables are met.

. Undertake these responsibilities in the project:

i. Develop Cognitive AI modules for predictive maintenance, prescriptive OEE recommendations and dynamic planning and scheduling, using industrial machine and production data.

ii. Develop and deploy the Agentic AI Orchestrator (local LLM with function calling and API routing) to support natural-language decision support across internal and external systems.

iii. Support the design and implementation of the Two-Layer API data architecture for IT/OT data fusion, and its integration with the 3D Digital Twin and the commercial MES showcase.

iv. Validate the platform on SIT's testbed using industry partner data, and prepare technical reports, technology disclosures and publications.

v. Provide technical guidance to student assistants working on the project.

. Carry out Risk Assessment, and ensure compliance with Work, Safety and Health Regulations.

. Coordinate procurement and liaison with vendors/suppliers.

. Work independently, as well as within a team, to ensure proper operation and maintenance of equipment.

Job Requirements:

• Have a PhD in Electrical Engineering, Computer Science, Artificial Intelligence or a related field.
• Have relevant competence in applying AI/machine learning to industrial or engineering systems, such as data-driven modelling, condition monitoring, predictive analytics and optimisation.
• Proficient in Python for data processing, model development and validation.
• Knowledge of large language models, agentic AI, API development or digital twin technologies will be advantageous.
• A track record of peer-reviewed publications will be advantageous.

Key Competencies:

• Able to build and maintain strong working relationships with people within and external to the university.
• Self-directed learner who believes in continuous learning and development
• Proficient in technical writing and presentation
• Possess strong analytical and critical thinking skills
• Show strong initiative and take ownership of work