The Haber Lab in the Department of Environmental Health at Harvard University is looking for several highly motivated computational postdoc candidates to develop and apply novel data science methods to analyze cutting-edge genomic data, particularly single-cell RNA sequencing, spatial transcriptomics, multi-omics, and emerging data modalities.
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. Our work uses cutting edge genomics and computational methods to answer major questions in the field: for example, how do the airways of the lungs detect danger signals, such as allergens, viruses, or toxins, and trigger an immune response?
Past work has focused on discovering new cell types in the lungs (Nature, 2018), single-cell genomics of the small intestine (Nature, 2017), and using single-cell methods to describe how the immune system regulates stem cells (Cell, 2018). The successful candidate(s) will join an interdisciplinary team spanning the Harvard T.H. Chan School of Public Health (HSPH), Brigham & Women's Hospital, and the Broad Institute of MIT and Harvard.
- As a postdoc in the lab you will join, lead, and propose projects in the lab which use computational and systems biology approaches to analyze high-dimensional next-gen sequencing data. Typically, these datasets will derive from from samples of human lungs, and also from mouse models of airway injury, inflammation and regeneration, and aim in particular 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.
- The successful candidate will collaborate closely with clinical pulmonologists and immunologists to analyze new experimental data, generate hypotheses and plan new experiments.
- PhD or equivalent in computational biology, machine learning, data science, artificial intelligence, computer science, statistics, mathematics, or other 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
- Experience developing algorithms and/or conducting statistical analyses with large datasets, particularly genome-wide assays such as RNA-seq
- Knowledge of lung biology, mucosal immunology, biology of allergy, impact of environmental conditions on respiratory health
As a postdoc, you will meet regularly with Dr. Haber at HSPH in Harvard University’s Environmental Health Department. You will also interact regularly with faculty at Harvard-affiliated Hospitals, particularly Brigham & Women's 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.
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.