Research Fellow, Statistics, Department of Paediatrics
The National University of Singapore invites applications for a postdoctoral research fellow in Statistics in the Department of Pediatrics, Yong Loo Lin School of Medicine. The position focuses on new statistical methodology motivated by data from the cohort studies GUSTO (Growing Up in Singapore Towards healthy Outcomes) and S-PRESTO (Singapore PREconception Study of Long-Term Maternal and Child Outcome). Potential topics include but are not limited to network models and Gaussian graphical models. The candidate will work closely with Prof. Maria De Iorio (email@example.com).
Appointments will be made on a 2 year contract basis in the first instance, with the possibility of extension.
Purpose of the post
The Research Fellow (RF) will work closely with, the Principal Investigator and team members for the development of Bayesian methodology and computational algorithm.
Main Duties and Responsibilities
The successful candidate is expected:
- to develop statistical theory and methodology for network/graphs models;
- to contribute to the analysis of high dimensional data sets deriving from the cohort studies GUSTO (Growing Up in Singapore Towards healthy Outcomes) and S-PRESTO (Singapore PREconception Study of Long-Term Maternal and Child Outcome);
- to prepare and present findings of research activity to colleagues for review purposes;
- to contribute to the overall activities of the research team;
- to carry out any other duties as are within the scope, spirit and purpose of the job, the title of the post and its grading as requested by the line manager;
- the postdoctoral researchers are expected to focus on scientific research, but may also be required for a light teaching duty;
- maintain the highest standard of professional conduct and record keeping in accordance with policies and procedures;
- Assist with any other duties of a similar nature that are delegated by the PI.
The applicant should:
- hold a PhD in Statistics or closely related field
- possess a good knowledge of Bayesian inference and Bayesian computational tools such as MCMC and SMC
- programming skills in R, MATLAB and one of C/C+ or equivalent
- experience of working in a research environment
- ability to work well with academic colleagues at all levels
- ability to communicate outcomes of work, including policy impact, to a range of academic and other (particularly policy) audiences
- ability to work independently and in collaboration
- ability to manage time and work to strict deadlines
Remuneration will be commensurate with the candidate’s qualifications and experience.
Only shortlisted candidates will be notified.
Location: Kent Ridge Campus
Organization: Yong Loo Lin School of Medicine
Department : Paediatrics
Employee Referral Eligible: No
Job requisition ID : 10056