Postdoctoral Fellow-MSH-32910-036

Mount Sinai; United States; On-site; USD 55,000 - 70,000; Full time

Job summary

Mount Sinai seeks a Postdoctoral Fellow in Human Genomics to lead independent research on the genetics and genomics of complex traits and rare disorders under the supervision of Dr. Nathalie Chami.

You will integrate large-scale genetic data with EHR, proteomics, and other deeply phenotyped datasets to understand genetic architecture and disease heterogeneity. The role focuses on moving beyond gene discovery to understand penetrance, subtypes, mechanisms, and comorbidities to advance precision

Qualifications

• PhD required in human genetics, statistical genetics, genetic epidemiology, bioinformatics, computational biology, biostatistics, or closely related field.
• Strong quantitative and analytical skills for complex genetic analyses.
• Experience analyzing human genetic or genomic data.
• Proficiency in R and Unix/Linux environments.
• Strong understanding of statistical principles in genetic and epidemiologic research.
• Ability to independently analyze data and troubleshoot analyses.
• Excellent scientific writing and communication skills.

Responsibilities

• Lead independent research projects from study design through analysis, interpretation, and publication.
• Analyze large-scale genomic datasets including GWAS, exome, whole-genome sequencing, and rare-variant data.
• Integrate genomic data with clinical, EHR, proteomic, and multi-omics datasets.
• Develop and implement rigorous statistical and computational methods for human genetic studies.
• Interpret findings in disease biology and potential clinical relevance.
• Prepare manuscripts and present findings at scientific meetings.
• Contribute to grant applications and new research directions.
• Collaborate with investigators across genetics, epidemiology, clinical medicine, bioinformatics, and data science.

Skills

Strong quantitative skills

Statistical genetics knowledge

Proficiency in R

Unix/Linux experience

Experience with GWAS

Polygenic risk scores

Fine-mapping/colocalization

High-performance computing

Education

PhD in human genetics or related field

Job description

Postdoctoral Fellow - Human Genomics

Position Overview

We are seeking a highly motivated Postdoctoral Fellow with extensive experience in statistical genetics/genetic epidemiology to join our research program focused on the genetics and genomics of complex traits and rare disorders under the supervision of Dr. Nathalie Chami.

Our research integrates large-scale human genetic and genomic data with electronic health records, proteomics, multi-omics, and other deeply phenotyped datasets to understand the genetic architecture and biological heterogeneity of complex disease.

A major focus of the lab is moving beyond gene discovery to understand disease penetrance, subtypes, mechanisms, and comorbidities, with the long-term goal of advancing precision medicine.

Research Areas

• Genetic discovery for obesity, diabetes, cardiovascular disease, and related cardiometabolic traits
• Genome-wide association studies (GWAS) and fine-mapping
• Rare-variant association analyses using whole-exome and whole-genome sequencing
• Integration of rare and common genetic variation
• Polygenic risk scores and genetic modifiers of disease penetrance
• Genetic and molecular characterization of disease subtypes
• Multi-ancestry and cross-population genetic analyses
• Integration of genomics with proteomics and other multi-omics data
• Genetics of longitudinal clinical outcomes and electronic health record-derived phenotypes
• Integration of genomic and imaging-derived traits
• Causal inference and translation of genetic discoveries into biological and clinical insight

Responsibilities

• Lead independent research projects from study design through analysis, interpretation, and publication
• Analyze large-scale genomic datasets, including GWAS, exome sequencing, whole-genome sequencing, and rare-variant data
• Integrate genomic data with clinical, EHR, proteomic, multi-omic, and other phenotypic datasets
• Develop and implement rigorous statistical and computational approaches for human genetic studiesInterpret genetic findings in the context of disease biology and potential clinical relevance
• Prepare manuscripts for publication in peer-reviewed journals and present findings at national and international scientific meetings
• Contribute to grant applications and development of new research directions
• Collaborate with investigators across genetics, epidemiology, clinical medicine, bioinformatics, data science, and related disciplines

Required Qualifications

• A PhD in human genetics, statistical genetics, genetic epidemiology, bioinformatics, computational biology, biostatistics, or a closely related field
• Strong quantitative and analytical skills
• Experience analyzing human genetic or genomic data
• Proficiency in R
• Experience working in Unix/Linux computational environments
• Strong understanding of statistical principles relevant to genetic and epidemiologic research
• Ability to independently analyze data, critically interpret results, and troubleshoot analytical problems
• Strong scientific writing and communication skills
• Demonstrated ability to work both independently and collaboratively
• Experience in statistical genetic including GWAS , Whole-exome or whole-genome sequencing analysis
• Polygenic risk scores
• Fine-mapping, colocalization, or other post-GWAS analyses
• Large-scale biobank datasets
• High-performance computing and reproducible computational workflows
• A strong publication record and evidence of the ability to take scientific ownership of a project are highly valued.

Desired Attributes

• Scientifically curious and creative
• Highly motivated and intellectually independent
• Interested in asking biologically and clinically meaningful questions using human genomic data
• Rigorous and thoughtful in quantitative analysis
• Proactive and able to move projects forward independently
• Collaborative and comfortable working in multidisciplinary teams
• Organized, dependable, and committed to reproducible research
• Interested in developing toward scientific independence

Research Environment and Career Development

The fellow will work in a highly collaborative environment at the intersection of human genetics, genomics, epidemiology, computational biology, and precision medicine. The position provides access to large-scale genomic and deeply phenotyped datasets and opportunities to collaborate with investigators across multiple disciplines. A major emphasis wil