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University of Michigan is seeking a researcher to advance integration of cancer genomics with AI to build interpretable clinical models. The role focuses on training and validating deep learning models with multi-omics and imaging data to predict relapse and therapy responses.
Responsibilities include preprocessing sequencing data (DNA-seq, RNA-seq, ChIP-seq, ATAC-seq, single-cell, etc.) and downstream analyses.
The position focuses on the integration of cancer genomics and advanced AI approaches to develop biologically interpretable clinical models. Key responsibilities include training, fine-tuning, and validating deep learning models using multi-omics and imaging data to predict clinical outcomes such as cancer relapse and targeted therapy responses. Additional duties include preprocessing of various sequencing data types (DNA-seq, RNA-seq, ChIP-seq, ATAC-seq, single cell, etc) as well as downstream statistical analyses. Development of genomic and epigenetic analyses and data portals utilizing Oxford Nanopore based data will be a focus of this position.
The position requires a minimum of bachelor's degree in either Bioinformatics, Genomic and Genetics, or related Data Sciences.
Prior experience in analyzing third generation sequencing data and interfacing with traditional analyses in Pathology is preferred. M.S. degree in either Bioinformatics, Genomic and Genetics, or related Data Sciences.
Michigan Medicine is one of the largest health care complexes in the world and has been the site of many groundbreaking medical and technological advancements since the opening of the U-M Medical School in 1850. Michigan Medicine is comprised of over 30,000 employees and our vision is to attract, inspire, and develop outstanding people in medicine, sciences, and healthcare to become one of the world’s most distinguished academic health systems. In some way, great or small, every person here helps to advance this world-class institution. Work at Michigan Medicine and become a victor for the greater good.