Research Fellow (Computer Science / Finance / Economics)
The Climate Transformation Programme (CTP) aims to develop, inspire and accelerate knowledge-based solutions and educate future leaders to establish the stable climate and environment necessary for resilient, just, and sustainable Southeast Asian societies.
CTP will generate knowledge and innovation across disciplines including climate and Earth science, ecology, materials science, artificial intelligence, humanities, social sciences and the arts, finance, health, and engineering. It will also translate state-of-the-art scientific results into real world solutions for Singapore, and it will transfer these solutions to Southeast Asia (SEA) and beyond.
As part of this programme, Cluster 5 Climate and finance markets will measure and price climate risk in financial markets, design innovative risk financing solutions to climate change, and quantify economic impact of climate policies.
The Research Fellow will be based in the Nanyang Business School and will contribute to interdisciplinary research under Cluster 5, with a particular emphasis on empirical analysis, AI-enabled data construction, and policy-relevant research outputs.
Duties And Responsibilities
We regret that only shortlisted candidates will be notified.
Hiring Institution: NTU
CTP will generate knowledge and innovation across disciplines including climate and Earth science, ecology, materials science, artificial intelligence, humanities, social sciences and the arts, finance, health, and engineering. It will also translate state-of-the-art scientific results into real world solutions for Singapore, and it will transfer these solutions to Southeast Asia (SEA) and beyond.
As part of this programme, Cluster 5 Climate and finance markets will measure and price climate risk in financial markets, design innovative risk financing solutions to climate change, and quantify economic impact of climate policies.
The Research Fellow will be based in the Nanyang Business School and will contribute to interdisciplinary research under Cluster 5, with a particular emphasis on empirical analysis, AI-enabled data construction, and policy-relevant research outputs.
Duties And Responsibilities
- Design, develop, and execute empirical research projects related to climate risk, financial markets, and climate policy, in alignment with the objectives of Cluster 5: Climate and Finance Markets under the Climate Transformation Programme.
- Construct, clean, and analyze large-scale datasets combining financial, environmental, and policy information, including both structured and unstructured data sources.
- Apply artificial intelligence and large language model (LLM) tools to extract, structure, and analyze information from unstructured sources such as corporate disclosures, regulatory filings, policy documents, and project-level reports.
- Develop and maintain retrieval-augmented generation (RAG) pipelines and related AI-enabled research workflows to support dataset construction, empirical analysis, and evidence synthesis.
- Implement rigorous empirical and quantitative methods to measure and price climate-related risks in financial markets and to assess the economic and financial impacts of climate policies.
- Contribute to the preparation of academic manuscripts for submission to leading peer-reviewed journals, as well as policy-oriented reports and research outputs.
- Collaborate closely with faculty investigators, research staff, and interdisciplinary partners across the University and with external collaborators.
- Support project coordination activities, including documentation of research workflows, version control of code and data, and supervision or mentoring of research assistants where appropriate.
- PhD (or PhD near completion) in Computer Science, Finance, Economics, or a related quantitative discipline.
- Strong training in quantitative, empirical, or computational research methods.
- Experience working with large-scale datasets, including unstructured text data.
- Familiarity with AI and large language model (LLM) tools; experience with retrieval-augmented generation (RAG) frameworks is an advantage.
- Strong programming skills (e.g., Python, R, or similar).
We regret that only shortlisted candidates will be notified.
Hiring Institution: NTU