Research Fellow / Research Engineer (AI and Data Analytics for Food and Nutrition Systems) - MM3

Singapore Institute of Technology

Singapore

On-site

SGD 60,000 - 90,000

Full time

11 days ago

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Job summary

Singapore Institute of Technology seeks a Research Fellow / Research Engineer to advance data-driven modelling, optimisation, and decision-support tools for food and nutrition systems. You will work with the PI on analytics, ML, and computational modelling to deliver industry-relevant outcomes.

The role offers exposure to publications, technical development, and collaboration with industry partners within SIT’s Food, Chemical and Biotechnology division.

Qualifications

  • Bachelor’s or Master’s degree in Engineering, Computer Science, Data Science, Applied Mathematics, Statistics, Operations Research, Industrial Engineering, Food Science or related discipline.
  • Applicants with a PhD may be considered for appointment as Research Fellow.
  • Interest or experience in food systems, nutrition, sustainability, supply chains, or related domains is advantageous.
  • Good programming skills in Python or other relevant languages.
  • Experience in data analysis, modelling, machine learning, optimisation, software development, or scientific computing is advantageous.
  • Strong analytical, problem-solving, and quantitative skills.
  • Ability to learn new methods and tools independently.
  • Good written and verbal communication skills.

Responsibilities

  • Support the research project to ensure milestones and deliverables are achieved.
  • Collect, organise, process, and analyse datasets from various sources.
  • Develop computational models, data analytics workflows, and decision-support tools.
  • Conduct data analysis, visualisation, model validation, and performance evaluation.
  • Assist in the development and testing of machine learning and optimisation models.
  • Support the integration and analysis of food, nutrition, sustainability, and related datasets.
  • Prepare technical reports, research documentation, presentations, journal publications, and conference materials.
  • Support student projects and other research activities related to the project.
  • Assist in project coordination, progress reporting, and research administration.

Skills

Python
Data analysis
Machine learning
Optimization

Education

Bachelor’s degree in Engineering/CS/Data Science/Mathematics
Master’s degree in a related field
PhD considered for appointment

Job description

Research Fellow / Research Engineer (AI and Data Analytics for Food and Nutrition Systems) - MM3

Posting Start Date: 09/10/2026

Schemes of Service: Research

Division: Food, Chemical and Biotechnology

Employment Type: Fixed Term

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 Research Fellow / Research Engineer will support a research project focused on the development of data-driven modelling, optimisation, and decision-support tools for food and nutrition systems. The successful candidate will work closely with the Principal Investigator on research activities involving data analytics, computational modelling, machine learning, and optimisation. The role offers opportunities to contribute to research publications, technical development, and industry-relevant project outcomes in the areas of food sustainability, nutrition, and supply chain decision-making.

Key Responsibilities
  • Support the research project to ensure milestones and deliverables are achieved.
  • Collect, organise, process, and analyse datasets from various sources.
  • Develop computational models, data analytics workflows, and decision-support tools.
  • Conduct data analysis, visualisation, model validation, and performance evaluation.
  • Assist in the development and testing of machine learning and optimisation models.
  • Support the integration and analysis of food, nutrition, sustainability, and related datasets.
  • Prepare technical reports, research documentation, presentations, journal publications, and conference materials.
  • Support student projects and other research activities related to the project.
  • Assist in project coordination, progress reporting, and research administration.
  • Follow SIT requirements on data management, research integrity, intellectual property, cybersecurity, and workplace safety.
  • Communicate with relevant internal or external stakeholders to support project activities and deliverables.
  • Any ad-hoc duties assigned by the Supervisor.
Job Requirements
  • Bachelor’s or Master’s degree degree in Engineering, Computer Science, Data Science, Applied Mathematics, Statistics, Operations Research, Industrial Engineering, Food Science, Nutrition, or a related discipline.
  • Applicants with a PhD may be considered for appointment as Research Fellow.
  • Interest or experience in food systems, nutrition, sustainability, supply chains, or related application domains is advantageous.
  • Good programming skills in Python or other relevant programming languages.
  • Experience in data analysis, modelling, machine learning, optimisation, software development, or scientific computing is advantageous.
  • Strong analytical, problem-solving, and quantitative skills.
  • Ability to learn new methods and tools independently.
  • Good written and verbal communication skills.
  • Ability to work independently and collaboratively in a research environment.
  • Strong organisational skills and ability to manage multiple tasks and meet project deadlines.
Key Competencies
  • Proficient in Python or equivalent programming languages for data analysis and modelling.
  • Strong analytical, problem-solving, and quantitative skills.
  • Ability to develop and validate computational models and data-driven solutions.
  • Good written and verbal communication skills, with the ability to prepare technical reports and presentations.
  • Self-motivated, able to work independently, and committed to continuous learning.
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