Postdoc: Cancer Genomics & AI for Multi-Omics Models

NAACPJobFinder; Ann Arbor (MI); Hybrid; USD 60,000 - 80,000; Full time

Benefits offered by this job

Hybrid or remote work options

Excellent health benefits

Job summary

University of Michigan invites applications for a Postdoctoral Research Fellow position in the Michigan Center for Translational Pathology. The role focuses on integrating cancer genomics with AI to build interpretable clinical models and develop a clinico-genomic database for pediatric and adult cancers.

The candidate will train deep learning models on multi-omics data, build data portals, and collaborate across pathology and computational teams while preparing high-impact manuscripts.

Qualifications

• PhD in a relevant field with cancer biology experience.
• Demonstrated publication track record.
• Strong communication, analytical and collaborative skills.

Responsibilities

• Process and preprocess raw data across genomics, proteomics and epigenomics.
• Develop analyses and data portals utilizing Nanopore data.
• Perform cross-platform omics analyses to identify phenotype-genotype associations.
• Train and validate deep learning models on multi-omics and imaging data.
• Develop analytical pipelines and a clinico-genomic database and web resources.
• Collaborate with pathology teams and prepare manuscripts for publication.

Skills

Bioinformatics

Cancer biology

Publication track record

Communication skills

Analytical skills

Team collaboration

Education

PhD in Bioinformatics or related field

Tools

Oxford Nanopore sequencing data analysis

Job description

University of Michigan invites applications for a Postdoctoral Research Fellow position in the Michigan Center for Translational Pathology. The role focuses on integrating cancer genomics with AI to build interpretable clinical models and develop a clinico-genomic database for pediatric and adult cancers.

The candidate will train deep learning models on multi-omics data, build data portals, and collaborate across pathology and computational teams while preparing high-impact manuscripts.