Research Assistant (Surgery)

National University of Singapore; Singapore; On-site; SGD 42,000 - 66,000; Full time

Job summary

The Yong Yoo Lin School of Medicine at the National University of Singapore is seeking a full-time, experienced research assistant to develop and evaluate breast cancer risk prediction models in Singapore. The role offers opportunities to contribute to cutting-edge cancer research and collaborate with a multidisciplinary team.

You will develop and extend prediction models, assist with grant proposals, ethics submissions, and contribute to publications.

Qualifications

• Bachelor's or Master's degree in a relevant field (Statistics, Biostatistics, Engineering, Economics, Pharmacy, Public Health, or CS).
• Experience with quantitative research, preferably cancer prediction models.
• Strong analytical and data management skills with EMR and observational data.
• Experience with statistical software (R) and programming languages (R, C/C++, Python).
• Excellent written and verbal communication; ability to work independently and in a team.

Responsibilities

• Conduct high-quality research and draft grant proposals or contribute to small grant proposals.
• Develop and extend cancer risk prediction models.
• Support ethics applications.
• Contribute to peer-reviewed publications and other outputs, including as lead author.
• Review latest research on breast cancer risk and survivorship; disseminate findings at conferences.
• Participate in mandatory NUS training and stay updated on methods.

Skills

Quantitative research

Data management

Written communication

Verbal communication

Independent work

Team collaboration

Time management

Education

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

Tools

R

Python

C/C++

Job description

Company description:

The National University of Singapore is the national research university of Singapore. Founded in 1905 as the Straits Settlements and the Federated Malay States Government Medical School, NUS is the oldest higher education institution in Singapore

Job description:

The Yong Yoo Lin School of Medicine (YYLSoM) 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

• 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.

Competencies

Clearly communicates Faculty's/Department's policiesFaculty members' concerns are handled well by the incumbent and his/her team of administrators