The Welch Laboratory at the University of Michigan is seeking a research investigator to develop and apply algorithms, machine learning methods, and statistical models for analysis of single-cell genomic data. Our research focuses on enabling biological discovery by applying novel computational approaches to genomic data. Broadly, we seek to understand what genes define the complement of cell types and cell states within healthy tissue, how cells differentiate to their final fates, and how dysregulation of genes within specific cell types contributes to human disease. The lab publishes in high-impact journals, including Cell, Nature, and Nature Biotechnology.
This position will focus on methods for analyzing and integrating single-cell RNA-seq, single-cell epigenome data, and spatial transcriptomic data as part of several NIH-funded projects. We have data and biological collaborators from several different systems, including mouse bone, mouse brain, and human hematopoietic stem cells. This is such an exciting and fast-moving field that Nature Methods recently selected "Single-Cell Multimodal Omics Analysis" as the Method of the Year 2019 and "Spatial Resolved Transcriptomics" as Method of the Year 2020.
A unique benefit of this position is the rich set of collaborative opportunities available, allowing truly interdisciplinary projects. Our collaborative network includes bench scientists and computational method development colleagues within the Single-Cell Analysis Program, the Michigan Neuroscience Institute, and the Michigan Institute for Data Science (MIDAS). Additional opportunities for collaboration are available with faculty in the Artificial Intelligence Laboratory in the Department of Computer Science and Engineering.
Doctoral degree or its equivalent in professional and technical experience.
Two or more years of postdoctoral work.
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