Post-doctoral position available (with flexible start dates) to develop novel machine learning/computational biology approaches to model and understand mammalian microbiomes. Projects include elucidating fundamental rules governing the formation and maintenance of complex microbial ecosystems in the mammalian gut under the National Science Foundation funded project, MTM2: The rules of microbiota colonization of the mammalian gut project (https://gerber.bwh.harvard.edu/mtm-2-the-rules-of-microbiota-colonization-of-the-mammalian-gut) and developing novel computational methods to analyze longitudinal microbiome data under the NIGMS R01 “Bayesian Machine Learning Tools for Analyzing Microbiome Dynamics.”

The position will give you the opportunity to develop advanced machine learning/computational biology methods while working on real, biologically relevant problems. Techniques we use include Bayesian nonparametric models, dynamical systems inference from sparse data, interpretable models, approximate inference methods and relaxations of discrete variables to enable fully-differentiable models.

The candidate is expected to engage with the broader machine learning and computational biology communities by presenting work at top conferences, as well as publishing applications of new methods in high impact journals. Although some experience modeling biological or other complex systems is required, microbiome specific knowledge is not required. This could be a good fit for either someone with a strong machine learning background who wants to get domain-specific research experience, OR someone with a strong mathematical background who wants to get more machine learning experience.

Qualifications

• PhD in computer science, computational biology, applied mathematics, statistics, or other quantitative discipline
• Excellent publication track record
• Strong mathematical background with track record developing novel models and methods
• Solid programming skills in Python; this isn’t a software engineering job, but you will need to be able to develop efficient implementations and apply your work to real biological data
• Experience modeling biological or other complex systems required; microbiome experience desirable, but not required
• Superior communication skills and ability to work on multidisciplinary teams
• Ability to reside in the U.S. and legally work in the country; there is an opportunity to work remotely during the COVID-19 pandemic, but funding sources require the post-doc to work in the U.S.