Postdoctoral Associate Computational Biology

Our interdisciplinary research group uses machine learning and genomics to study the immunology of environmental health and particularly physiological mechanisms of lung inflammation and asthma. We use cutting edge genomics and computational methods to answer major questions in the field: how do the airways of the lungs detect danger signals such as allergens viruses or toxins and trigger an immune response Which are the most important types of sentinel cells that are on the lookout for danger in inhaled air and able to co-ordinate an effective defense 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:

• As a postdoc in the lab you will join lead and propose projects in the lab that use computational and systems biology approaches to analyze high-dimensional next-gen sequencing data. Typically these datasets will derive from samples of human lungs and also from mouse models of airway injury inflammation and regeneration and aim to examine the impact of environmental exposures - particularly air pollution and allergens - on the lungs.
• Develop new statistical methods and algorithms to mine these data to map out complex pathways of cellular communication between the lungs and the local immune system defining aspects that are aberrant in disease to discover new possible therapies.
• Collaborate closely with other computational scientists clinical allergists pulmonologists and immunologists to develop new approaches analyze new experimental data generate hypotheses and plan new experiments.

Essential Qualifications:

• PhD or equivalent in computational biology machine learning data science artificial intelligence computer science statistics mathematics or another quantitative field.
• Candidates holding a degree in biological or medical science are also welcome to apply if they have strong background in computational or statistical work.
• Strong interpersonal and communication skills experience presenting and communicating research.
• Excellent problem solving and quantitative analysis skills

Additional Qualifications:

• Experience developing algorithms and/or conducting statistical analyses with large datasets particularly genome-wide assays such as RNA-sequencing
• Knowledge of lung biology immunology mucosal immunology biology of allergy impact of environmental conditions on human health

Mentoring

As a postdoc you will meet regularly with Dr. Haber and other faculty at Broad/HSPH particularly in Harvard Universitys Environmental Health and also Biostatistics Departments. You will also interact regularly with faculty at Harvard-affiliated Hospitals particularly Brigham & Womens Hospital and the Broad Institute participate in regular group meetings and will participate in meetings of research teams spanning institutes and hospitals throughout the Boston area.

Working at Broad