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 where you will be part of the research team to develop/produce/investigate generative AI aided safety investigation system. The project is a collaboration with SMRT to create a transportation-specific LLM, structured into three work packages. These include transportation safety investigation data preparation, focused on collecting and synthesizing data related to the transportation domain. The second package involves transportation safety LLM construction, aiming to develop highly adaptable models that not only comprehend information but also prove utility in addressing real-world challenges in the field of transportation safety. The third package is dedicated to real transportation investigation inference and feedback, aiming to better align LLMs with accurate transportation investigations.
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:
- Contribute to the development of data crawlers for collecting transportation investigation-related data from websites
- Conduct research on generative models and implement technology accordingly
- Prepare technical reports and scientific publications
- 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 postgraduate degree in computer science, data science or AI
- Have relevant knowledge in machine learning or natural language processing
- Have relevant knowledge in software engineering and Python programming
- Having relevant working experience in research or development will be advantages
