Researcher/Engineer (Artificial Intelligence/Machine Learning) Job at Singapore Institute of Technology (SIT)

AI and ML Jobs

As an applied learning university, SIT works closely with industry in its research activities. Research staff have the opportunity to develop applied research skills relevant to industry demand while working on SIT research projects.

The primary responsibility of this role is to deliver an innovative research project for industry where, as part of a research team, you will develop the first AI-assisted integrated NDT validation system that will deliver ±10% accuracy at 95% confidence to validate the reusability of structural steel. The key innovation will be to use AI to analyze larger datasets and integrate complex mechanical properties obtained from DT and electrical/magnetic permeability data obtained from NDT to build multi-parameter machine learning (ML) models that predict key material properties of reusable steel.

Primary Responsibilities

  • Participate in and manage research projects with the Principal Investigator (PI), Co-PIs and members of the research team to ensure all project deliverables are met.
  • Responsibilities for the project include:
  • Building a test result database: We conduct both DT and NDT on the same samples to create a comprehensive dataset for AI model development, manage the data collection process on collaborators' factory sites, and ensure the accuracy and integrity of the collected data.
  • Statistical model development: The DT results are utilized to develop statistical models to estimate mechanical properties based on normal distribution, and statistical data are analyzed to support model development.
  • AI model development and validation: Different regression models are developed to evaluate their feasibility and suitability, and model fitting and validation phases are conducted using training and testing datasets to ensure that the selected model meets the accuracy criteria (±10% at 95% confidence) for individual mechanical properties and overall classification results (grade determination).
  • Validation of the method: Implement the proposed method and AI model on a testbed case, measure the impact of the method in terms of time and cost savings, and develop implementation guidelines based on the validation results.
  • Carry out risk assessments and ensure compliance with occupational health and safety regulations.
  • Coordinate procurement and liaise with vendors/suppliers.
  • Works independently as well as within a team to ensure proper operation and maintenance of equipment.
  • Publish research findings in peer-reviewed journals and present at conferences.
  • Assist with preparing project reports, proposals and documentation.


  • Possess relevant competence in the areas of structural engineering, materials science, statistics and programming fundamentals.
  • Degree in civil engineering, mechanical engineering or materials science. Master's or PhD degree is an advantage.
  • Knowledge of AI/ML and common ML programming languages ​​will be an advantage.

Key Competencies

  • You will be able to build and maintain strong working relationships with people both within and outside the University.
  • Self-directed learners who believe in continuous learning and growth
  • Proficient in technical writing and presentations
  • Possess strong analytical and critical thinking skills
  • Demonstrate strong initiative and take responsibility for work
  • You can perform data pre-processing and develop statistical and regression models.
  • Have knowledge of the mechanical properties of structural steels and the factors that affect their performance
  • Able to prioritize tasks, meet deadlines and manage multiple responsibilities.

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