Job Description
Applications are invited for the following full-time position in the Saw Swee Hock School of Public Health: Research Assistant (Cancer Epidemiology and Prediction)
The Saw Swee Hock School of Public Health (SSHSPH) at the National University of Singapore (NUS) is recruiting a full-time, experienced Research Assistant to develop and evaluate breast cancer risk prediction models in cancer study in Singapore. This role offers the opportunity to contribute to cutting-edge research, collaborate with a team of experts, and work on cancer research.
Job scope:
- To undertake high-quality research, including contributing to drafting major grant proposals and/or leading in drafting small grant proposals;
- To develop and extend cancer risk prediction models;
- To support ethics applications;
- To contribute to peer-reviewed publications and other outputs, including as lead author;
- Contribute to drafting grant proposals and co-authoring publications.
- To review the latest research on breast cancer risk, prognosis and survivorship studies.
- To disseminate research findings through presentations at regional and international conferences.
- To contribute to the broader research community through journal and grant reviews.
- To participate in mandatory NUS training and keep abreast of advancements in research methods.
Qualifications
Requirements:
- Bachelor's or Master's degree in Statistics, Biostatistics, Engineering, Economics, Pharmacy, Public Health, or Computer Science.
- Experience with quantitative research, preferably related to cancer prediction models.
- Strong analytical and data management skills using electronic medical records and observational data.
- Experience with statistical software (e.g., R) and programming languages (e.g., R, C/C++, Python).
- Excellent written and verbal communication skills.
- Ability to work independently and collaboratively within a team.
- Strong organizational skills and time management.
The following knowledge and experience would be advantageous:
- Experience contributing to research grant applications.
- Experience with analysis of data from epidemiological study designs.
- Experience with data analysis using statistical inference techniques.
- Experience with health economic evaluations.
- Experience with parallel and/or high-performance computing.
The grade of appointment will be accorded based on candidate’s academic qualifications and years of relevant experience.
Applicants should send the following documents during application:
- Cover letter highlighting career goals and relevant experience
- Curriculum Vitae, containing details of three named referees
Please note that only shortlisted candidates will be contacted.
