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Jobs in Singapore   »   Jobs in Singapore   »   Education / Training Job   »   Research Assistant in Energy Studies Institute (Automated Carbon Solution)
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Research Assistant in Energy Studies Institute (Automated Carbon Solution)

National University Of Singapore

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Interested applicants are invited to apply directly at the NUS Career Portal.

Your application will be processed only if you apply via NUS Career Portal.


Energy Studies Institute (ESI)

The Energy Studies Institute (ESI) is a research institute at the National University of Singapore seeking to advance the understanding of energy policy issues by conducting independent research and analysis. We are looking for researchers to join a multi-disciplinary team carrying out research projects on a range of energy issues that concern Singapore and the region.

ESI has an opening for a Research Assistant to ensure the timely delivery of research and policy recommendations with national, regional and/or international clients. Candidates are expected to be highly familiar with data analytics, visualization and the deployment of modern computer science techniques, ideally including an awareness of emerging digital technologies and trends in automated data capture. Candidates will also need to demonstrate a robust understanding of principles and techniques for carbon accounting and foot printing. An understanding of Singapore’s economic system and local work experience is desirable. The appointed candidate is also expected to have a sound awareness of current and emerging trends in energy and environmental research.

Job Description

Commensurate with experience, and working as part of a team, tasks may include the following:

  • To report on the motivations for and expanded adoption of socially responsible business practices, including carbon disclosure, either voluntarily or in response to evolving national/international policies e.g. reacting to carbon tax revisions or similar;
  • To review regional and international best practices for carbon footprint measurement, including the scope of emissions captured;
  • To work with the hybrid infrastructure management platform as the central component of a high-integrity automated carbon footprint management solution;
  • To explore the potential for, and possibly support the development of, a digital twin architecture built upon a hybrid infrastructure management platform, as a framework for strategic evaluation of carbon footprint policies;
  • To support the development of virtual reality software for integrated simulation extensions of the hybrid infrastructure management platform output, accessed through APIs;
  • To explore the development of a lifecycle management algorithm around the critical elements of data centre cooling system architecture(s);
  • To document case studies for the use of automated technologies in carbon emissions data capture, verification and/or reporting.

Job Requirements

  • Possess a Bachelor's degree in computer science, data science or other related fields
  • Applicants should have demonstrated experience in quantitative data analysis.
  • Relevant experience with Python and deep learning libraries such as Keras, Tensorflow and Pytorch
  • A robust awareness of principles for carbon footprint analysis and reporting.
  • A good contemporary understanding and interest in energy and environmental issues.
  • Track record of publications in reputable journals would be an advantage.
  • Have a strong written and oral command of the English language.
  • Able to work independently and as part of a team.

Application Process

To apply for this position, please combine the following documents in 1 PDF and attach it under the CV column when submitting your application:

  • Curriculum vitae.
  • A cover letter, of no more than 800 words, explaining the applicant’s past research experience and aptitude in relation to the research project.

Interested candidates, please submit your application with all the required documents. Only shortlisted applicants will be notified.


Shortlisted applicants may be called for interview, either in person or by zoom, as appropriate. If you have not heard from us within 3 months, you should assume that your application has not been successful.

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