Research Engineer (Carbon capture, Utilisation and Storage) - MM2

Singapore Institute of Technology; Singapore; On-site; SGD 60,000 - 95,000; Part time

Job summary

Singapore Institute of Technology invites a Research Engineer (Carbon capture, Utilisation and Storage) to join a cross-disciplinary team in a fixed-term role. You will collect data, build techno-economic models, and develop machine-learning surrogates for cost screening related to CO2 maritime transport.

Applicants should hold a relevant degree and strong Python skills, with experience in data analysis and modelling.

Qualifications

• Bachelor’s or Master’s degree in Chemical Engineering, Energy Systems, Data Science, Computer Science, Environmental Engineering, Maritime Engineering, or related discipline.
• Good programming skills in Python.
• Experience in data analysis, scientific computing, modelling, or software development.
• Knowledge of techno-economic analysis, energy systems, sustainability, CCUS, or maritime transport is preferred.
• Basic knowledge of machine learning, uncertainty analysis, or optimisation advantageous.
• Experience with web-based tools or dashboards such as Streamlit, Dash, Flask, or Plotly is desirable.
• Good written and verbal communication skills.
• Able to work independently and as part of a multidisciplinary research team.
• Able to manage tasks, meet deadlines, and produce well-documented work.

Responsibilities

• Support the research team and students to ensure project milestones and deliverables are met.
• Collect, clean, organise, and analyse data related to CO2 maritime transport, port operations, CO2 liquefaction, storage, vessel logistics, and regional CCUS value chains.
• Build and maintain a parameter registry with data sources, assumptions, parameter ranges, and confidence ratings.
• Develop and validate a bottom-up techno-economic analysis model for CO2 maritime transport.
• Conduct uncertainty analysis, scenario analysis, and sensitivity analysis for Singapore-linked CO2 transport corridors.
• Develop and test machine learning surrogate models for rapid cost screening.
• Prepare technical reports, research documentation, figures, presentations, journal manuscripts, and conference materials.
• Support student projects in data processing, model testing, visualisation, and prototype testing.
• Assist in project coordination, progress reporting, documentation, and research administration.
• Follow SIT requirements on data management, research integrity, intellectual property, cybersecurity, and workplace safety.
• Communicate with internal or external stakeholders to ensure project deliverables are met.
• Any ad-hoc duties assigned by Supervisor.

Skills

Python

Data analysis

ML basics

Uncertainty analysis

Data visualization

Education

Bachelor’s or Master’s degree

Tools

Streamlit

Dash

Flask

Plotly

Job description

Job Description

Research Engineer (Carbon capture, Utilisation and Storage) - MM2

Posting Start Date: 07/08/2026

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. Carbon capture, utilisation and storage (CCUS) refers to a suite of technologies that capture CO2 emissions from industrial or energy-related sources and either utilise the captured CO2 or transport it to secure geological formations for long-term storage. The Research Engineer will support a project that aims to develop a Singapore-calibrated, risk-aware modelling framework for cross-border CO2 maritime transport. The role will contribute to the development of techno-economic models, uncertainty analysis, machine learning surrogate models, and a prototype web-based calculator. The Research Engineer will work closely with a multidisciplinary project team with expertise in CCUS infrastructure modelling, maritime systems, techno-economic analysis, machine learning, uncertainty quantification, and industry translation.

Key Responsibilities

• Support the research team and students to ensure project milestones and deliverables are met.
• Collect, clean, organise, and analyse data related to CO2 maritime transport, port operations, CO2 liquefaction, storage, vessel logistics, and regional CCUS value chains.
• Build and maintain a parameter registry with data sources, assumptions, parameter ranges, and confidence ratings.
• Develop and validate a bottom-up techno-economic analysis model for CO2 maritime transport.
• Conduct uncertainty analysis, scenario analysis, and sensitivity analysis for Singapore-linked CO2 transport corridors.
• Develop and test machine learning surrogate models for rapid cost screening.
• Prepare technical reports, research documentation, figures, presentations, journal manuscripts, and conference materials.
• Support student projects in data processing, model testing, visualisation, and prototype testing.
• Assist in project coordination, progress reporting, documentation, and research administration.
• Follow SIT requirements on data management, research integrity, intellectual property, cybersecurity, and workplace safety.
• To communicate in any relevant internal or external stakeholders to ensure project deliverables are met.
• Any ad-hoc duties assigned by Supervisor.

Job Requirements

• Bachelor’s or Master’s degree in Chemical Engineering, Energy Systems, Data Science, Computer Science, Environmental Engineering, Maritime Engineering, or a related discipline.
• Good programming skills in Python.
• Experience in data analysis, scientific computing, modelling, or software development.
• Knowledge of techno-economic analysis, energy systems, sustainability, CCUS, or maritime transport is preferred.
• Basic knowledge of machine learning, uncertainty analysis, or optimisation is advantageous.
• Experience with web-based tools or dashboards such as Streamlit, Dash, Flask, or Plotly is desirable.
• Good written and verbal communication skills.
• Able to work independently and as part of a multidisciplinary research team.
• Able to manage tasks, meet deadlines, and produce well-documented work.

Key Competencies

• Proficient in Python or equivalent programming languages for data analysis, modelling, and scientific computing.
• Strong foundation in data analytics, numerical modelling, and data-driven decision support.
• Able to collect, organise, evaluate, and document data from multiple technical and public sources.
• Able to develop, test, and validate computational models in a structured and reproducible manner.
• Able to interpret modelling results, identify dominant cost drivers, and communicate uncertainty clearly.
• Able to prepare high-quality technical reports, figures, presentations, and research documentation.
• Able to work independently while maintaining effective communication with the research team and stakeholders.
• Able to build and maintain positive working relationships within and outside the university.
• Self-directed learner with strong initiative, ownership, and commitment to continuous learning.
• Possess strong analytical thinking, problem-solving skills, and attention to research quality.