Research Fellow in Biochemistry
[National University of Singapore Department of Biochemistry


The National University of Singapore invites applications for a Post-Doctoral Fellow with Data Analytics skills, able to handle Big Genomics Data, for the project on ‘Integrative Approach to identify Clinically Relevant Genetic Markers / Molecules and Gene Networks as potential therapeutic targets or Diagnostic / Prognostic Biomarkers’ in the Department of Biochemistry, Yong Loo Lin School of Medicine.

The Department of Biochemistry is committed to employ ‘better analytics to explore new opportunities in the context of better-defined systems of interest’ so as to usher in the new era of ‘High Definition Biochemistry (HD BCH). Appointments will be on a 2-year contract in the first instance, with the possibility of extension.

Purpose of the post

The Post-Doctoral Fellow (PDF) will be responsible to, and work closely with the Principal Investigator (PI), other members of the laboratory as well as clinical and scientific collaborators to ensure the successful completion of the project. The PDF principal role is to develop a pipeline to analyze and integrate big data from various genomic, proteomic, etc, as well as clinical data of the patients.

He/she will also develop algorithms incorporating Artificial Intelligence (AI) to predict prognosis or response to therapy of these patients from the integration of the various data from the patient. If the PDF has the requisite bench skills, he will also validate the prediction experimentally.

Main duties and responsibilities

The Post-Doctoral Fellow will be responsible for the following:

Be a leader of the project working closely with the PI and other members of the laboratory as well as clinical and scientific collaborators to ensure that the appropriate data is collected and key relevant scientific / clinical issues are being addressed
Be updated on the latest literature on the research focus and how our research can help fill the gaps in knowledge or solution to the clinical problem

Responsible for addressing the computational needs (including hardware and software) required for big data analyses.
Responsible for analyzing (including developing a pipeline) and integrating various types of ‘omics’ and clinical data to uncover potential biomarkers for early diagnosis/prognosis/response to therapy of the patients

Responsible for developing new algorithms (including incorporating AI) to predict prognosis / response to therapy of the patients
Train/Teach juniors in the laboratory as well as attachment students in big data analyses, etc

Write manuscripts for publication consideration on research
Write and/or assist in writing grants for continued support of research
Have opportunity to compete for funding (e.g. Graduate Innovation Program, GRIP) and be trained in entrepreneurship to facilitate the establishment of a start-up company on valuable algorithms developed or biomarkers identified in the laboratory.

Have opportunity to present research in meetings (local/overseas)
Provide support towards new NUSMed / NUHS initiative through NUHS Research Office, likely in the field of data analyses
Assist in any other duties delegated by the PI

The applicant should:

Have a PhD degree with documented experience in handling Big Data.
Experience in the following will be an added advantage:
Big genomics data analyses from Next-generation sequencing platforms

Artificial Intelligence (AI) experience
Setting up systems to facilitate big data analyses.
Has good communication skills

Be able to work independently as well as in a team, have an investigative nature, attention to detail; and

Fresh PhD graduates who are passionate about employing big data approaches to make a difference clinically are very welcome
Remuneration will be commensurate with the candidate’s qualifications and experience.

Informal enquiries are welcome and should be made to A/Prof Caroline Lee, at

Formal application: If you are passionate about employing big data approaches to make a difference clinically and have the required qualifications, 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 3 referees) to:

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