Postdoctoral Associate (Cancer)
Core
Develop and implement computational approaches to analyze high-throughput genomic and epigenomic data to identify epigenetically regulated programs contributing to hematological malignancies.
Role type
Postdoctoral Associate (Computational Biology/Bioinformatics)
Builds
Integrated cancer risk prediction models, cancer subtype discovery pipelines, and single-cell RNA-Seq analysis frameworks.
Domain
Oncology / Computational Biology / Genomics
Deliverable
production ML models
Required skills
R/Bioconductor, Python/Perl, next-generation sequencing (NGS) data analysis, statistics, Linux/Unix, scripting, epigenome biology
Preferred skills
experience with epigenome-wide assays, single cell RNA-Seq, non-coding RNA data analysis
Technologies
RNA-Seq, ChIP-seq, HiC-Seq, ATAC-Seq, R, Bioconductor, Perl, Python
Responsibilities
Analyze high-throughput genomic and epigenomic datasets; develop computational models for cancer risk prediction and subtype discovery; characterize epigenetic changes in hematologic malignancies; write manuscripts independently.
Seniority
Postdoctoral Researcher