Breast Cancer Risk Prediction Research Assistant

National University of Singapore; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

National University of Singapore's Saw Swee Hock School of Public Health invites applications for a Research Assistant (Cancer Epidemiology and Prediction). This full-time position focuses on developing and evaluating breast cancer risk prediction models using Singaporean study data.

You will contribute to grant proposals, collaborate with a research team, publish outputs, and keep up with advances in cancer epidemiology.

Qualifications

• 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.

Responsibilities

• 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.

Skills

Statistics

Biostatistics

Data analysis

R

Python

C/C++

Communication

Teamwork

Education

Bachelor’s or Master’s degree in Statistics, Biostatistics, Engineering, Economics, Pharmacy, Public Health, or Computer Science

Job description

Job Title: Research Assistant (Cancer Epidemiology and Prediction)

University-Level Unit: Saw Swee Hock School of Public Health

Faculty/Department-Level Unit: Saw Swee Hock School of Public Health

Employee Category: Research Staff

Location_ONB: Kent Ridge Campus

Posting Start Date: 21/07/2026

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.

Req ID: 33772