We are a computational and systems biology group that is also directly engaged in trials with human participants. We aim to obtain a mechanistic and actionable understanding of the microbiome's role in human pathophysiology, using machine learning, metabolic modeling, and network inference. We operate in an engaging and multi-disciplinary environment consisting of computational biologists, applied mathematicians, statisticians, physicists and physicians. Working at the intersection between computational biology and medicine, the lab develops algorithms and computational methods that aim to understand microbial growth, activity, and metabolite production, and then proceeds to apply these methodologies as the basis for clinical inquiries in diverse settings.
We are always interested in adding talented and motivated individuals to our team!
Postdoctoral Research Fellows
We are seeking postdoctoral researchers who want to work in a creative and collaborative environment on new algorithmic approaches for inferring the activity and dynamics of microbial communities.
Ph.D. in any quantitative science (such as statistics, computer science, physics, etc.), or a Ph.D. in the life sciences with a strong computational/quantitative background.
You will acquire any missing domain/biological knowledge with us.
Strong statistics or machine learning background especially valued.
Experience with assembly algorithms, flux balance analysis or network inference is valued but not required.
Excellent communication and organizational skills.
Ph.D. or M.D. Ph.D. students
Positions are available for Ph.D. or M.D.-Ph.D. students with experience and/or interest in data analysis, development of microbiome analysis methods or clinically-oriented microbiome research.
Positions are also available for undergraduate students with strong programming skills and for software developers.
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