Research Fellow (Intelligent Carbon Management)

National University of Singapore; Singapore; On-site; SGD 70,000 - 90,000; Full time

Job summary

A leading university in Singapore is seeking a full-time Research Fellow for carbon management R&D. The successful candidate will develop an activity-level carbon calculation methodology, lead the CognitionX Lab, and contribute to impactful research with industry collaborators. Ideal candidates will have a PhD and strong background in data science and ontologies, as well as excellent communication skills.

Benefits

Access to computing resources

Support for professional development

Opportunity to help build and lead a new lab

Qualifications

• PhD in Civil/Construction Engineering, Built Environment, Industrial/Systems Engineering, Environmental Engineering, Computer/Data Science, or Operations Research.
• Demonstrated R&D capabilities evidenced by high-quality publications or impactful projects.
• Strong proficiency in data science and programming, especially with Python.

Responsibilities

• Design and implement a scalable carbon calculation tool.
• Apply data science and optimization to recommend carbon reduction strategies.
• Publish findings in leading journals and prepare technical reports.

Skills

Data science

Programming (Python)

Ontologies/knowledge graphs

Communication skills

Project management

Education

PhD in a relevant field

Tools

Python (pandas, NumPy, scikit-learn)

Graph databases (e.g., Neo4j)

Job description

Job Description

The National University of Singapore (NUS) Department of the Built Environment (DBE) invites applications for a full-time Research Fellow to drive R&D in carbon management and optimization within the built environment. The successful candidate will lead the development of an activity-level carbon calculation methodology and digital tool that automatically tracks emissions across project lifecycle, integrating data science, ontologies/knowledge graphs, and carbon accounting. The Research Fellow will help develop and lead the CognitionX Lab ( https://cognitionx-lab.github.io/) with Dr. Jinying Xu, Assistant Professor and Director of the Cognition X Lab, contributing to a high-impact research agenda and industry collaborations.

Key Responsibilities

• Tool and methodology development
  • Design and implement a scalable activity-level carbon calculation tool, including data ingestion, estimation algorithms, and automated reporting.
  • Build and maintain ontologies/knowledge graphs mapping activities, materials, equipment, emission factors, and data provenance.
  • Develop data pipelines integrating BIM/IFC, schedules (4D), IoT/telemetry, procurement/ERP, and emissions factor databases.
• Analytics and optimization
  • Apply data science, uncertainty quantification, and optimization/operations research to evaluate and recommend carbon reduction strategies under cost, schedule, and quality constraints.
  • Create decision-support dashboards and audit-ready logs aligned with recognised standards (e.g., GHG Protocol, ISO 14064/14067, PAS 2080, ISO/EN LCA standards).
• Research outputs and impact
  • Publish in leading journals and conferences; prepare technical reports, software documentation, and open science artefacts where permissible.
  • Contribute to grant proposals, project scoping, and delivery of milestones; present findings to academic and practitioner audiences.
• Lab development and leadership
  • Co-develop the Cognition X Lab's technical roadmap and research priorities with Dr. Jinying Xu.
  • Lead day-to-day project management, mentor junior researchers/students, and ensure rigorous R&D practices.
  • Establish collaborations with internal and external stakeholders (industry partners, agencies, other labs).

What We Offer

• Access to computing resources, datasets, and industry case studies
• Support for professional development, conferences, and dissemination (subject to funding)
• Opportunity to help build and lead a new lab with a clear decarbonisation mission

Application Materials

Please submit the following as a single PDF in the application system by 20 December, 2025:

• Cover letter (max 2 pages) detailing fit, R&D experience, and vision for the Cognition X Lab's cognition for carbon mitigation and research agenda
• CV (including publications and software/projects) and academic transcripts
• Two representative work samples (e.g., journal paper, code repository, technical report, ontology/graph model)
• 4 Reference letters, including one from candidate's PhD supervisor
• PhD/Master/Bachelor degree certificate

Evaluation Criteria

• Depth and originality of R&D contributions
• Technical fit (data science, ontology/knowledge graph, carbon accounting, optimization)
• Leadership and collaboration potential for lab development
• Communication and project management skills

Shortlisted candidates will be invited for interviews.

NUS is committed to a diverse and inclusive research environment. We welcome applications from all qualified candidates.

Note: If you plan to align the tool with specific standards, datasets, or industry partner requirements, share those details and we can further tailor the scope, deliverables, and evaluation metrics.

Job Requirements

Minimum Qualifications

• PhD in a relevant field (e.g., Civil/Construction Engineering, Built Environment, Industrial/Systems Engineering, Environmental Engineering, Computer/Data Science, Operations Research).
• Demonstrated research and development capabilities, evidenced by high-quality publications, software/tools, or impactful projects.
• Strong proficiency in data science and programming (Python preferred; experience with pandas, NumPy, scikit-learn; SQL).
• Practical experience with ontologies/knowledge graphs (RDF/OWL, SHACL, SPARQL) and at least one graph database (e.g., Neo4j, GraphDB).
• Solid understanding of carbon calculation/accounting and LCA concepts (scope definitions, boundaries, emission factors, allocation, uncertainty).
• Excellent communication skills and ability to lead multidisciplinary teams and industry collaborations.

Preferred Qualifications

• Experiences in getting grants and writing grant proposals.
• Experiences in (co-)supervising students.
• Integration experience with BIM/IFC, project scheduling tools (e.g., Primavera/MS Project), and construction process data.
• Optimization expertise (linear/mixed-integer programming, stochastic optimization) and familiarity with simulation or decision analytics.
• Experience with cloud/data engineering (APIs, ETL, data quality), dashboarding (Power BI/Tableau), and software engineering (version control, testing, CI/CD).
• Knowledge of emissions databases (e.g., ecoinvent), EPDs, and international standards-aligned workflows; familiarity with Singapore's built environment context.

More Information

• Location: Kent Ridge Campus
• Organization: College of Design and Engineering
• Department: The Built Environment
• Employee Referral Eligible: No
• Job requisition ID : 31002