Job Description

Overview

We are seeking a motivated bioinformatician with a strong foundation in genomics to join our academic research team. The ideal candidate will work with large-scale GWAS data, genomic annotations (including spatial transcriptomics), and associated summary data to build streamlined analysis pipelines and databases.

Key Responsibilities

• GWAS Data Management: Locate, download, and curate summary statistics from large-scale GWAS repositories.
• Annotation Integration: Identify and retrieve relevant genome annotations (e.g., gene models, epigenomic maps, spatial transcriptomics) to support post-GWAS analyses.
• Database Development: Develop a consistent, queryable database for GWAS and annotation data.
• Genomic Data Analysis: Process genotype and sequencing data, perform quality control, and derive polygenic inferences.
• Pipeline Automation: Collaborate in building and maintaining automated workflows for downstream analyses.

Required Qualifications

• Education: Ph.D. in Bioinformatics, Computational Biology, Human Genetics, or related field, or a Master’s degree with 4 years of relevant experience.
• Genomics Expertise: Solid understanding of GWAS, variant QC, imputation, and polygenic risk scoe.
• Programming Skills: Proficiency in Python, R, and Linux shell scripting.
• Data Handling: Experience with large genomic datasets using tools such as PLINK, BCFtools/VCFtools, and public databases (e.g., Ensembl, GWAS Catalog).
• Computing: Experience with HPC or cluster computing environments.

Preferred Skills

• Experience with workflow management systems (Nextflow, Snakemake).
• Familiarity with SQL or noSQL database systems.
• Knowledge of cloud computing environments and containerization (Docker/Singularity).
• Exposure to single-cell and spatial transcriptomics data analysis.

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