Bioinformatician II: Multi-Omics & AI-Driven Genomics

Mount Sinai; United States; On-site; USD 110,000 - 150,000; Full time

Job summary

Mount Sinai in the United States seeks a genetic epidemiologist/statistical geneticist to join its computational genomics team as Bioinformatician II. The candidate will lead large-scale genetic analyses, develop scalable pipelines, and collaborate on biobank-scale and EHR-linked projects.

The role requires proficiency in R, Python, and Unix/Linux shell scripting, experience with GWAS, PRS, and multi-omics, and a track record of reproducible workflows. AI/ML experience is a plus.

Qualifications

• MS/PhD in a relevant genomics or computational field with biology exposure.
• Strong computational and analytical skills with experience handling large genomic datasets.
• Experience with reproducible workflows and version control (Git/GitHub).
• Familiarity with cloud and HPC environments is a plus.

Responsibilities

• Perform large-scale genetic analyses including QC pipelines, GWAS, and rare variant studies.
• Construct polygenic risk scores and perform fine-mapping and integrative genomics.
• Analyze proteomics and multi-omics datasets and link to clinical data.
• Develop scalable pipelines using R, Python, and shell scripting.
• Collaborate with national/international consortia and prepare manuscripts and reports.

Skills

R

Python

Shell scripting

ML

Education

MS in Bioinformatics/Computational Biology/Genomics

MS in computation with biology exposure

PhD preferred

Bachelors + postgraduate experience considered

Tools

PLINK

SAIGE

Regenie

BOLT-LMM

GCTA

LDSC

KING

bcftools

samtools

vcftools

RStudio

Python

JupyterLab

Job description

Mount Sinai in the United States seeks a genetic epidemiologist/statistical geneticist to join its computational genomics team as Bioinformatician II. The candidate will lead large-scale genetic analyses, develop scalable pipelines, and collaborate on biobank-scale and EHR-linked projects.

The role requires proficiency in R, Python, and Unix/Linux shell scripting, experience with GWAS, PRS, and multi-omics, and a track record of reproducible workflows. AI/ML experience is a plus.