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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.