Machine learning/computational biology postdoctoral fellows needed immediately to work in the Center for Clinical and Translational Metagenomics at Harvard Medical School in the research group of Dr. Georg Gerber (http://gerber.bwh.harvard.edu). The successful applicant will develop and apply novel statistical/machine learning methods to:
- Infer dynamic behaviors of the microbiota in human subjects and experimental animal systems
- Infer microbe-microbe and host-microbe interaction networks in natural and synthetic biology systems
- Predict host phenotypes, including disease status in patients, from static or longitudinal microbiome and host immune system data
Qualifications:
- PhD in computer science, applied mathematics, statistics, or other highly quantitative discipline from top institution
- Previous experience performing high-quality machine learning/statistical research using Bayesian methods
- Strong mathematical abilities with track record creating novel models and inference algorithms
- Some previous experience modeling biological systems (microbiome experience desirable, but not required)
- Experience implementing and running algorithms in high-performance parallel computing environments
- Excellent publication track record
- Excellent ability to communicate complex ideas and work on multidisciplinary teams with others not versed in machine learning/statistical methods
Applications will be accepted until the position is filled, although priority will be given to applications received by April 15, 2015.
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Applications without a cover letter responsive to this posting will not be considered.
