-
computational software tools for the lab, support efforts of the research team, train students and postdocs, contribute to data management and analysis, and innovate computational methods for metabolomics
-
to attract self-motivated and talented researchers who work well in a team environment. The successful candidate will work closely with the lab's graduate students and postdocs to develop reproducible
-
coupling, using machine learning. The postdoc will be expected to collaborate with other postdocs at Princeton and with other members of the M2LInES project across multiple institutions. In addition to a
-
computational software tools for the lab, support efforts of the research team, train students and postdocs, contribute to data management and analysis, and innovate computational methods for metabolomics
-
, using machine learning. The postdoc will be expected to collaborate with other postdocs at Princeton and with other members of the M2LInES project across multiple institutions. In addition to a
-
the lab’s graduate students and postdocs to develop reproducible bioinformatics workflows for addressing fundamental questions about the ecology and evolution of microbial species within the gut microbiomes
-
researchers who work well in a team environment. The successful candidate will work closely with the lab's graduate students and postdocs to develop reproducible bioinformatics workflows for addressing
-
ability to proactively manage deadlines *Excellent ability to seamlessly interact with diverse stakeholders: the PI, trainees (undergraduate, graduate, postdocs, high school students), collaborators