Postdoctoral Position in Computational Biology and Environmental Health

Boston, Massachusetts
Salary range is $56,000 to $64,008, commensurate with experience.
March 31 2021
Position Type
Full Time
Organization Type

Departments of Environmental Health & Biostatistics, Harvard T.H. Chan School of Public Health

The Haber Lab in the Harvard T.H. Chan School of Public Health has an opening for up to two Postdocs in two project areas investigating asthma. Asthma is the most common chronic disease of childhood and highly disparate by race and social class. Household allergens, particularly mold, are amongst its strongest risk factors, and a key driver of its disparities. Research in the lab develops novel computational and statistical approaches to answer questions about how mold triggers asthma, from biological mechanisms to the epidemiology of its social determinants. 

  1. Using single-cell analysis determine how cells in the airways of the lung sense allergens. Asthma is often triggered by environmental exposures to inhaled allergens which interact with cells lining the lungs called the airway epithelium. Fundamental questions about this process remain unanswered, such as: how does the lung sense allergens and transduce that information to trigger immune responses which lead to asthma attacks? Research in our group aims to answer this question by developing and applying new computational approaches to analyze single-cell transcriptomics and other next-generation sequencing data collected from mouse and human lungs. 
  2. Using city-wide data to identify sites of exposure to household allergens that trigger asthma. An extensive literature has shown that poor housing quality, particularly exposure to mold and pests, is a primary cause of asthma disparities, and crucially, that removing or repairing the bad conditions dramatically improves asthma outcomes. Unlike outdoor air pollution however, it is difficult to measure indoor air quality in a scalable, city-wide manner. This research direction develops approaches to identify dangerous housing at the level of individual complexes or buildings, by using machine learning, causal inference and geospatial analysis to examine asthma burden at high spatial and temporal resolution while controlling for patient and neighborhood characteristics. 

In your application, please include a cover letter that introduces yourself, gives context for your application, and describes your interests in either one or both of these two projects.

Essential Qualifications:

  • PhD or equivalent in computational biology, computer science, epidemiology, statistics, mathematics, or other quantitative field.
  • Candidates holding a degree in biological/medical science are also welcome to apply if they have extensive background in computational or statistical work. 

Additional Qualifications:

  • Applicants must have substantial experience with statistical or epidemiologic data analysis. Preference will be given to candidates with demonstrated research interests in areas currently under investigation (e.g. asthma, COPD, lung biology, mucosal immunology) in the research group.
  • Experience and/or training in geospatial analysis, Bayesian disease mapping and other methods, spatial epidemiology
  • Strong quantitative analysis skills and experience developing algorithms and/or conducting statistical analyses with large datasets, particularly genome-wide assays such as RNA-seq
  • Knowledge of lung physiology, immunology, biology of allergy, exposure science or environmental health

Equal Opportunity Employer

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, gender identity, sexual orientation, pregnancy and pregnancy-related conditions or any other characteristic protected by law.

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