Postdoctoral Fellow-MSH-12756-010

Mount Sinai Health Systems•New York, NY
•$72,500 - $80,000

About The Position

The Department of Otolaryngology-Head and Neck Surgery at the Icahn School of Medicine at Mount Sinai seeks a highly motivated postdoctoral research fellow interested in environmental epidemiology, multi-omics integration, and bioinformatics. The fellow will join a multidisciplinary team studying how environmental exposures contribute to the development and progression of head and neck diseases. The research integrates large-scale epidemiological data with genomics, epigenomics, transcriptomics, and metabolomics to investigate molecular mechanisms of environmental health effects and disease susceptibility. The role is suited to someone with a background in environmental epidemiology, bioinformatics, computational biology, or biostatistics who can apply advanced statistical and computational approaches to study environmental exposures, molecular mechanisms, and disease. The fellow will have opportunities to lead research projects, develop analytical approaches, collaborate across disciplines, and contribute to scientific publications.

Requirements

  • A doctoral degree, such as a PhD or MD, is required; the qualifications specify a PhD in epidemiology, bioinformatics, biostatistics, computational biology, or a related field.
  • Strong statistical and computational skills, including proficiency in R and/or Python.
  • Experience analyzing complex epidemiological, high-dimensional biological, or multi-omics datasets.
  • Excellent analytical and problem-solving skills.
  • Strong scientific writing skills, including experience preparing manuscripts for peer-reviewed publication.
  • Ability to independently develop and execute research projects.
  • Ability to work on multiple concurrent projects.
  • Ability to work independently and collaboratively within a multidisciplinary research team.
  • Strong organizational and time management skills, with the ability to meet deadlines.

Nice To Haves

  • Experience in environmental epidemiology, molecular epidemiology, or exposure assessment.
  • Experience analyzing and integrating multi-omics data, including genomics, epigenomics, transcriptomics, proteomics, and/or metabolomics.
  • Experience with bioinformatics pipelines and computational tools for processing and analyzing omics datasets.
  • Knowledge of advanced statistical methods for high-dimensional data analysis, including machine learning and data integration approaches.
  • Experience combining molecular data with epidemiological and environmental exposure data.
  • Familiarity with causal inference and mediation analysis.
  • Experience working with large-scale population-based cohorts and complex epidemiological datasets.
  • A strong publication record and demonstrated ability to communicate scientific findings effectively.
  • Experience with grant writing or developing research proposals.

Responsibilities

  • Conduct large-scale statistical and bioinformatics analyses of epidemiological and multi-omics datasets.
  • Investigate associations between environmental exposures and head and neck diseases using advanced epidemiological and computational approaches.
  • Integrate environmental exposure, epidemiological, and multi-omics data to identify molecular pathways and biological mechanisms underlying disease risk.
  • Develop and apply statistical and computational methods for analyzing high-dimensional and multi-modal datasets.
  • Lead the preparation and publication of scientific manuscripts in peer-reviewed journals.
  • Present research findings at national and international scientific conferences.
  • Collaborate with epidemiologists, bioinformaticians, basic scientists, clinicians, and other researchers on multidisciplinary projects.
  • Contribute to grant applications and the development of research proposals.
  • Maintain well-documented and reproducible analytical workflows.

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What This Job Offers

Job Type

Full-time

Career Level

Senior

Education Level

Ph.D. or professional degree

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