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General information

Location
Cambridge, MA
Ref #
37118
Job Family
Research
Date published
16-Apr-2024
Time Type
Full time

Description & Requirements

The Infectious Disease and Microbiome Program (IDMP) is looking for a Group Leader in Computational Biology to lead and direct investigations into the mechanisms of host microbiome interactions in health and disease. We are an interdisciplinary group with expertise in computational analysis, microbiology and immunology. The candidate for this position will be working closely with computational and experimental biologists, graduate students, post docs and staff scientists to contribute with directing, planning, developing novel methods and executing the analysis of large multi-omic datasets with the goal of identifying microbes, genes or microbial products that are relevant to human health. The ideal candidate should be broadly experienced with analyzing next generation sequencing data, statistics, and machine learning, and should be willing to collaborate closely with computational postdocs for methods implementation, and with experimental team members for validation of computational results. Prospective applicants should have made significant contributions to their area of study, as evidenced by a strong publication record. We are seeking creative and highly motivated individuals who want to work in a dynamic, multi- disciplinary research environment.

RESPONSIBILITIES

  • Design and execution of small and large collaborative studies

  • Track record in developing new methods

  • Mentoring and supervision of scientists at various levels

  • Writing of publications, grants and reports

  • Maintaining up to date toolbox of computational methods

REQUIREMENTS

  • A Ph.D. in Computational Biology, Bioinformatics, or a related field
    *4-5 years postdoctoral experience in computational biology or equivalent industrial experience, preferably with direct involvement in human microbiome research

  • Experience managing or mentoring a team with demonstrated leadership skills

  • Proficiency in one or more statistical or scripting languages appropriate for scalable data
    analysis

  • Familiarity with functional genetic and/or genomic data, as indicated by publication record

  • Ability to clearly communicate scientific material and work collaboratively.