Research Assistant (Diagnostic Radiology)

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Assistant-%28Diagnostic-Radiology%29/32548-en_GB/st=188CD011B6DD33446DD894ED5225F5F61C096B93

We regret that only shortlisted candidates will be notified.

Job Description

The National University of Singapore invites applications for a Research Assistant in the Department of Diagnostic Radiology, Yong Loo Lin School of Medicine. The Department of Diagnostic Radiology is committed to advancing imaging sciences for precision medicine, with strengths in medical image analysis, neuroimaging, and AI-driven healthcare. Our faculty collaborates widely with engineering and computational sciences, and we host specialized research facilities including PET/CT imaging development and advanced image computing platforms. More information on the department is available at https://medicine.nus.edu.sg/meddnr/about-us-staff.html.

Appointments will be made on a one-year contract basis in the first instance, with the possibility of extension.

Purpose of the post

The Research Assistant (RA) will support projects in medical image analysis and AI-driven healthcare research, working closely with the Principal Investigator and research team. The RA's role will include assisting with data processing, algorithm development, and research support for ongoing imaging projects. Specifically, the RA will:

1. Support research activities in medical imaging and AI, including data curation, preprocessing, and analysis.
2. Assist in the development, testing, and validation of computational models for imaging applications.
3. Conduct literature reviews and contribute to the preparation of manuscripts, reports, and presentations.

Qualifications

The applicant should:

(a) Hold at least a Bachelor's degree in a relevant discipline (e.g., computer science, biomedical engineering, electrical engineering, or related fields).

(b) Have research interest or prior experience in areas such as medical imaging, computer vision, artificial intelligence, or machine learning.

(c) Be proficient in programming and data analysis, and familiar with common tools for image processing.

(e) Possess good written and verbal communication skills.

Remuneration will be commensurate with the candidate's qualifications and experience.

Only shortlisted candidates will be notified.