Senior Research Fellow, Quantitative Research Scientist - CHILD
An exciting position is available with the NUS Yong Loo Lin School of Medicine’s Centre for Holistic Initiatives for Learning and Development (CHILD) for an enthusiastic, collaborative senior research fellow (research scientist) with strong quantitative skills. The scientist will work within highly transdisciplinary teams across multiple projects aiming to support families and early child development. A primary, but not exclusive, focus would be the DADSCAN (Dads Advancing Data for development of Singaporean Children and Adolescents Now!) project. DADSCAN is a joint endeavor with A*STAR’s Singapore Institute for Clinical Sciences (SICS) that seeks to accelerate context-specific insights from world-class, population-based, parent-child cohorts towards scalable interventions, with a specific focus on the father’s role in preconception to early child health and development.
The incumbent would be primarily responsible for three main roles:
- Providing leadership and management of the DADSCAN Project in consultation with the PI, co-investigators, and scientific advisory board.
- Provide broad technical expertise on quantitative study design and data analysis needs within CHILD’s growing translational science portfolio of intervention studies and evaluations. This would include conducting and advising on power calculations, statistical analyses, and interpretation of findings.
- Conducting independent research on paternal and familial contribution to child physical and mental health and development with the goal of developing translatable and testable interventions for the Singaporean context.
The incumbent must have a strong passion for child health and rigorous translational public health science with a background that enables fluent trans-disciplinary cooperation, collaboration, and consultation. A broad understanding of quantitative methods across social and biological sciences is a must with deep experience in one or more domains. Experience managing studies including IRB submissions and research instrument development, working with interventional and non-interventional (cohort) follow-up studies, and managing highly diverse data (i.e. questionnaire, psychometric, behavioral, MRI, genomic, molecular) are essential. The incumbent must be flexible and pro-active in managing team work, multiple objectives, and deadlines.
In return, the incumbent will participate in highly dynamic and innovative work with the goal of improving the lives of families and children in Singapore using the best of data and methods from discovery and translational sciences. CHILD partners broadly with academic, public sector, and civil society stakeholders to deliver rigorous, practicable, and sustainable change. The incumbent will also have access to an unprecedented data source with multimodal data on parents and children from up to three longitudinal birth cohort studies (GUSTO, N = ~1200 enrolled; S-PRESTO, N = ~1000 enrolled; and MAMS, N = ~2000 anticipated) and a local and international network of clinicians, researchers, and practitioners. The incumbent will have opportunities to develop, conduct, and present original research as well as interact with local and global stakeholders. The incumbent will not have teaching responsibilities.
Please include in your application,
- A brief cover letter describing how training, experience, and character fit the described role,
- A CV
- 2 representative publications or scientific communication works (e.g. white paper).
Applicants who are near completion of their doctorate are eligible. The position will be open until filled. Apologies as only short-listed candidates will be notified.
- PhD in quantitative biomedical discipline e.g. Epidemiology, Biostatistics, Statistics, Bioinformatics, with experience in cohort studies.
- 3 years of relevant research, including concurrent with doctorate
- Strong project management skills
- Strong commitment to working and delivering results as a team
- Strong data and analytic visualization skills
- Strong knowledge of quantitative / statistical science principles including on inference, uncertainty, and/or decision science
- Familiarity with typical quantitative methods from both social science and biomedical disciplines
- Proficiency in a statistical programming language (e.g. R, Stata)
- Organized, detail oriented, able to communicate scientific concepts clearly
- Interests in reproducible science, translational science, interventions
- Research interests in child health and development, paternal factors
- General knowledge of neuroscience, physiology, health & behavior
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 presence is required.
Taking into consideration the health and well-being of our staff and students and to better protect everyone in the campus, applicants are strongly encouraged to have themselves 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 : 16864