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Research Assistant (Department of Ophthalmology)

NATIONAL UNIVERSITY OF SINGAPORE

Singapore

On-site

SGD 20,000 - 60,000

Full time

Today
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Job summary

A leading educational institution in Singapore is seeking a Research Assistant for machine learning projects in biomedical sciences. Responsibilities include conducting independent research and managing project administration. The ideal candidate holds a degree in computer science or related fields and possesses strong machine learning knowledge. This position is contract-based for one year with potential for extension.

Qualifications

  • Hold a Bachelor’s or master’s degree in relevant fields.
  • Be able to work independently and in a team.
  • Have strong knowledge of machine learning.

Responsibilities

  • Conduct machine learning projects independently under the PI.
  • Oversee the general management of the projects.
  • Provide administrative support to the project.

Skills

Machine learning
Biomedical informatics
Attention to detail
Teamwork
Independent work

Education

Bachelor’s or master’s degree in computer science, engineering, biomedical informatics, or data science
Job description

Interested applicants are invited to apply directly at the NUS Career Portal

Your application will be processed only if you apply via NUS Career Portal

We regret that only shortlisted candidates will be notified.

Job Description

The National University of Singapore invites applications for Research Assistant for “Machine learning for Cognitive AI for biomedical sciences” in the Department of Ophthalmology, Yong Loo Lin School of Medicine. The department’s current data science efforts focus on building consciousness inspired machine learning to improve generalization and robustness of AI in medicine. The department has strong computational and medical expertise and significant amount of medical data and computational resources. More information on the department is available at https://medicine.nus.edu.sg/medoph. Appointments will be made on a 1-year contract basis in the first instance, with the possibility of extension.

Purpose of the post

The Research Assistant (RA) will be responsible to, and work closely with, the Principal Investigator and study team members to ensure the successful completion of the machine learning projects on time. The RA’s principal role will be to work in computational project such as modeling building and algorithm development.

Main duties and responsibilities

The Research Assistant will liaise with the relevant personnel in department to smooth the process of research and will be accountable to the Principal Investigator (PI). The RA will be able to:

  1. Independently conduct machine learning in medicine or fundamental machine learning projects under instruction by the PI
  2. Oversee the general management of the projects.
  3. Provide administrative and secretarial support to the project, such as organizing regular meetings to maintain regular communication with other members of the research team
  4. Maintain the highest standard of professional conduct and record keeping in accordance with policies and procedures.
  5. Assist with any other duties of a similar nature that are delegated by the PI.
Qualifications

Qualifications

The applicant should:

  1. holds a Bachelor’s or master’s degree in computer science, engineering, biomedical informatics, data science, or related disciplines;
  2. be able to work independently and in a team, have an investigative nature, attention to detail;
  3. have strong knowledge of machine learning or biomedical informatics;
  4. have experiences in the fundamental machine learning or machine learning in medicine

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

Formal application: Please submit your application, indicating current/expected salary, supported by a detailed CV (including personal particulars, academic and employment history, complete list of publications/oral presentations and full contacts of three (3) referees to the NUS career portal.

We regret that only shortlisted candidates will be notified.

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