The Postdoc Associate will use a multi-disciplinary approach, including GRO-seq, RNA-seq, ChIP-seq, ATAC-seq, CRISPR-seq, single-cell RNA seq, and Hi-seq, machine learning to understand environment-gene interactions in metabolic diseases and cancer. The postdoc fellow will develop independent projects.
- Prepares samples and perform validation studies for omics analysis using genetic modified mouse models.
- Performs functional analysis to identify cancer metabolic reprogramming.
- Performs molecular biology experiments to identify oncopathways.
- Writes manuscript to report the findings.
- Documents experiments to ensure that work can be replicated by others.
- Attends department seminar and other scientific events.
- MD or Ph.D. in Basic Science, Health Science, or a related field.
- Experience in metabolism, cancer biology, epigenetics, and bioinformatics.
Baylor College of Medicine is an Equal Opportunity/Affirmative Action/Equal Access Employer.