Editorial summary

The company is seeking a Research Fellow at the Centre for Research in Health Systems Performance to contribute to Health Services and Data Science work. The role supports a project on developing Natural Language Processing and Item Response Theory–based systems for Patient Reported Outcomes Measurement. Applicants should apply via the NUS Career Portal; only shortlisted candidates will be notified. The position carries a monthly salary of 8,625.

This summary is AI-generated and may contain inaccuracies. Please refer to the full job description below.

Job description

[This job https://singapore.job-q.com/jobs/detail/research-fellow-centre-for-research-in-health-systems-performance-42841 first appeared in Job-Q.com on 13 Nov 2026]

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Fellow-%28Centre-for-Research-in-Health-Systems-Performance%29/31152-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

Research Fellow in Health Services and Data Science (Project: Development of Natural Language Processing and Item response Theory based systems for Patient Reported Outcomes Measurement)

Optimizing the performance of health systems is essential to ensuring the wellbeing and longevity of populations worldwide. Singapore is particularly well placed to lead research in this field as its health system has been consistently ranked as one of the best in the world based on independent evaluation with the Global Burden of Disease data. The Centre for Research in Health Systems Performance (CRiHSP) aims to advance research in this area within the Yong Loo Lin School of Medicine of the National University of Singapore (NUS) as the leading centre for research in health systems in Asia. CRiHSP will be composed of a multidisciplinary team of researchers in health systems (health services and policy researchers, data scientists, social scientists, and others), and administrators. It will provide an exciting and dynamic place in which people of diverse backgrounds collaborate towards the common goal of achieving excellence in Health Systems Research.

As part of this collaboration, CRiHSP is hiring a highly motivated and experienced postdoctoral researcher to lead a research project employing mixed-methods for the development of methods for measuring patient reported outcome measures in the population of Singapore based on the efficient application of Natural Language Processing and Item Response Theory to existing measurement systems working under the project Principal Investigator (PI), CRiHSP Director, Prof Jose M Valderas. The role provides a rare opportunity to work at the centre of this rapidly evolving field, shaping the future of healthcare and clinical practice.

The responsibilities include:

• Managing and leading the proposed research project, including the conduct of data analyses, focusing on calibration of Patient Reported Outcome Measures using advanced psychometric methods and publication and dissemination;
• Establishing an independent research programme derived from the current project;
• Providing support for other collaborative, multidisciplinary research within CRiHSP and DFM;
• Contribution to course design and teaching; and

• Mentoring of students and junior researchers.

Please note that this job description is not intended to be exhaustive. Duties and responsibilities outlined may be amended during appointment, in light of changing circumstances. In addition to these duties, the post holder will be expected to be flexible in their role as the CRiHSP´s capacity evolves.

NUS offers highly competitive remuneration packages. The successful applicant will be offered an annual salary plus benefits commensurate with his or her qualifications, experience and expertise and will have access to travel support to disseminate research outcomes at international academic conferences.

The position is a 1-year full-time appointment at the academic rank of Research Fellow. An option to renew the appointment for subsequent years will depend on performance and continued funding for the project. There is the possibility to move to tenure track depending on performance.

Qualifications

A recognized Doctoral degree in a relevant discipline (Health Services Research, Public Health, Statistics, Psychometrics, Psychology or a closely related field)

Experience

• • Demonstrated experience in Natural Language Processing (NLP) and/or Item Response Theory (IRT) methods (essential)
  • Demonstrated experience in programming languages such as R, Python, and familiarity with NLP tools and techniques (essential)
  • Proven track record in handling and analyzing large healthcare dataset (essential)
  • Track record of publishing in international peer-reviewed journals (essential)
  • Researchers with existing research activities related to developing and using computerized adaptive (CAT) methods are particularly encouraged to apply.

Skills and Personal Attributes

• • Strong communication skills in English, both written and spoken (essential)
  • Strong leadership skills with the ability to work independently and as part of a multidisciplinary team (essential)
  • Highly developed problem-solving skills and adept at managing complex datasets (essential)
  • Ability to generate and maintain an independent stream of funding (essential)
  • Outcome-orientation with excellent organizational and project management skills, and attention to detail (essential)
  • Ability to work with culturally diverse populations (essential)

Interested candidates should submit a detailed CV (personal particulars, academic and employment history, full list of publications, contacts details of three (3) referees) and cover letter outlining their motivation and suitability for the project addressing each of the criteria outlined above via NUS Career Portal. Only shortlisted candidates will be notified. Applications will be considered on a rolling basis until a suitable candidate is found. 

Informal enquiries are welcome and should be made to .

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