Research Associate (Data Engineer)

NATIONAL UNIVERSITY OF SINGAPORE; Singapore; On-site; SGD 60,000 - 80,000; Full time

Job summary

A leading educational institution in Singapore invites applications for a Research Associate (Data Engineer). The role involves managing clinical databases, deploying algorithms, and performing data analysis. Ideal candidates should possess a Master’s in Data Science or related field, proficiency in SQL and programming languages such as Python or R. This role is pivotal in advancing machine learning and AI applications for clinical translation in biological ageing research, offering competitive compensation aligned with experience.

Qualifications

• Master's degree or equivalent in relevant field required.
• Strong programming skills in SQL, Python and/or R.
• Experience with clinical data analysis and interpretation required.

Responsibilities

• Organise and manage clinical databases in SQL.
• Build data systems to reduce manual data processing.
• Collaborate with data scientists to design and analyse experiments.
• Communicate research findings through publications and presentations.

Skills

SQL

Python

R

Data analysis

Machine learning

Artificial intelligence

Bioinformatics

Database management

Communication

Problem-solving

Education

Master’s degree in Data Science, Computer Science, or Biomedical Informatics

Professional certification in Data Engineering

Job description

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

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

We regret that only shortlisted candidates will be notified.

Job Description

The National University of Singapore invites applications for Research Associate (Data Engineer) in the Department of Biochemistry, Yong Loo Lin School of Medicine. Specifically, utilising data science approaches involving machine learning and artificial intelligence, A/Prof Gruber’s team focuses on the development and validation of biological ageing clocks for clinical translation and application. Appointments will be made on a two-year contract basis, in the first instance, with the possibility of extension.

Purpose of the post

The successful candidate should have a strong background in database administration, management and warehousing, as well as advanced machine learning, artificial intelligence, and bioinformatics techniques. Specifically, he or she will be responsible for curating and organising existing clinical databases, assist with the deployment and validation of algorithms using these databases, and related data analysis. The ideal candidate will have a strong understanding of SQL and expertise in programming languages such as Python and/or R.

Main Duties and Responsibilities

The Research Associate will be mainly responsible for the organisation and management of clinical databases, work with other team members to deploy biological ageing clock algorithms, and support the implementation of data systems and analytics pipelines for longitudinal trials in these databases. He or she will be accountable to the Principal Investigator (PI). The Research Associate will be able to:

1. Organise and manage clinical databases (in SQL), as well as liaise with external collaborators to maintain data operability and regulatory compliance;
2. Build data systems to reduce manual data processing and integrate warehousing;
3. Develop and apply computational models, algorithms, and tools to analyse and interpret large-scale clinical datasets;
4. Collaborate with data scientists to design and analyse experiments, and interpret results;
5. Stay up-to-date on new computational methods and tools, and apply them to ongoing research projects;
6. Communicate research findings through publications, presentations, and reports.

Qualifications

The ideal applicant should:

1. Have a Master’s degree or equivalent in Data Science, Computer Science, or Biomedical Informatics;
2. Professional certification or equivalent in Data Engineering;
3. Strong programming skills in SQL, Python and/or R;
4. Experience with clinical data analysis and interpretation;
5. Excellent communication and collaboration skills;
6. Strong problem-solving skills and ability to work independently;
7. Prior experience with biomedical and clinical data, especially in the context of age-dependent diseases and ageing would be advantageous.

Remuneration will be commensurate with the candidate’s qualifications and experience. Informal enquiries are welcome and should be made to A/Prof Jan Gruber at [e-mail].

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.