Research Assistant (Pharmacy and Pharmaceutical Sciences)

National University of Singapore; Singapore; On-site; SGD 20,000 - 60,000; Full time

Job summary

A prestigious university in Singapore is seeking a research candidate to work on a Genome-wide Association Study (GWAS) focusing on DEXA phenotypes. Responsibilities include performing GWAS, implementing analysis pipelines, and preparing manuscripts. Candidates should hold an MSc or BSc in relevant fields and have proficiency in genome-wide analysis tools and statistical modeling. Prior experience in population genetics is preferred.

Qualifications

• Prior experience in GWAS, population genetics, or multi-omics data analysis preferred.
• Familiarity with DXA/BIA phenotypes or SG100K/UK Biobank datasets will be an advantage.

Responsibilities

• Performing large-scale genome-wide association studies (GWAS) of DEXA-derived body composition traits.
• Implementing quality control (QC) and meta-analysis pipelines using PLINK2, REGENIE, and METAL.
• Identifying and interpreting novel ancestry- and sex-specific loci influencing fat distribution.
• Preparing manuscripts, figures, and supplementary materials for publication and conference presentations.

Skills

Proficiency in genome-wide analysis tools (PLINK2, REGENIE, METAL)

Statistical modeling (R/Python)

Linux-based HPC or cloud environments (e.g., DNAnexus, Lifebit)

Education

MSc or BSc in a relevant discipline such as Genomics, Bioinformatics, Biostatistics, Computational Biology, 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 successful candidate will work with Dr Liu Boxiang on the Genome-wide Association Study (GWAS) of DEXA phenotypes using the SG100K dataset, focusing on the genetic architecture of body composition traits in a multi-ethnic Asian cohort.

The main responsibilities of the position include:

• Performing large-scale genome-wide association studies (GWAS) of DEXA-derived body composition traits (e.g., fat and lean mass).
• Implementing quality control (QC) and meta-analysis pipelines using PLINK2, REGENIE, and METAL.
• Identifying and interpreting novel ancestry- and sex-specific loci influencing fat distribution.
• Preparing manuscripts, figures, and supplementary materials for publication and conference presentations.

Qualifications

Qualifications / Discipline:

• MSc or BSc in a relevant discipline such as Genomics, Bioinformatics, Biostatistics, Computational Biology, or Data Science.

Skills:

• Proficiency in genome-wide analysis tools (PLINK2, REGENIE, METAL), statistical modeling (R/Python), and Linux-based HPC or cloud environments (e.g., DNAnexus, Lifebit).

Experience:

• Prior experience in GWAS, population genetics, or multi-omics data analysis preferred.
• Familiarity with DXA/BIA phenotypes or SG100K/UK Biobank datasets will be an advantage.