Research Fellow, Health District, Risk-Based Segmentation
The National University of Singapore invites applications for a Research Fellow position, based in the Yong Loo Lin School of Medicine, Centre for Healthy Longevity, who will work in collaboration with the partners of the Health District @ Queenstown
The National University Health System (NUHS), the National University of Singapore (NUS) and the Housing & Development Board (HDB), together with multiple stakeholders from the public, private and people sectors, established the first-of-its-kind collaboration to develop the Health District @ Queenstown to create integrated solutions to enhance the health and well-being of residents across their life stages. Interventions implemented in the Health District @ Queenstown will be community driven, multi-sectoral and evidence informed, with due considerations of their efficacy, sustainability and scalability. The Health District @ Queenstown is a long-term project with potential to scale initiatives to other parts of Singapore, influence national policies, and generate knowledge and best practices for the benefit of local and international communities.
A major objective of the Health District @ Queenstown is to promote healthy longevity – to increase residents’ health span, i.e. the time residents spend in good health for as long as possible. The Research Fellow will work in a multidisciplinary team developing personalised precision health profiles by use of risk-based segmentation for ageing, cancer and metabolic diseases using longitudinal, large scale quantitative measurements of clinical data and circulating small molecules, proteins and genetic profiles. The segmentation will lead to the identification of individuals at risk for negative outcomes and identification of individuals at need for interventions to eventually develop optimal personalized preventive health strategy.
The Research Fellow will be part of the multidisciplinary team of researchers and clinicians of the Health District to:
- Collate evidence regarding risk-segmentation in general populations via literature searches
- Establish the infrastructure for clinical and biological data collection
- Analyse datasets
- Help writing grant proposals and ethics applications
We seek applicants who are well-versed in population studies and/or molecular & cellular sciences. Preference will be given to those who have a track record of achievement that spans these areas, and who have excellent personal & management skills.
Appointments will be on a 1-year contract in the first instance, with the possibility of extension subject to performance and mutual agreement.
- PhD in Medicine, or Biology or Epidemiology.
- Experience in supervision of human cohort studies would be advantageous.
- Must have experience in clinical and biological data analyses.
- Able to work independently and as a team member.
- Good interpersonal skills with strong leadership attributes.
- Must be meticulous and have good organization skills.
Please submit your application, indicating current/expected salary, supported by a detailed CV (including personal particulars, academic and employment history, complete list of publications/oral presentations and full contacts of 3 referees), and your location.
At NUS, the health and safety of our staff and students are one of our utmost priorities, and COVID-vaccination supports our commitment to ensure the safety of our community and to make NUS as safe and welcoming as possible. Many of our roles require a significant amount of physical interactions with students/staff/public members. Even for job roles that may be performed remotely, there will be instances where on-campus presences are required.
In accordance with Singapore's legal requirements, unvaccinated workers will not be able to work on the NUS premises with effect from 15 January 2022. As such, job applicants will need to be fully COVID-19 vaccinated to secure successful employment with NUS.
Location: Kent Ridge Campus
Organization: Yong Loo Lin School of Medicine
Department : Dean's Office (Medicine)
Employee Referral Eligible: No
Job requisition ID : 11942