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Computational Biologist

United States 61000.00 - 80000.00 USD / Year · Job Posted December 09, 2025
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Job Description

The Lauberth Lab in the Department of Biochemistry & Molecular Genetics at Northwestern University Feinberg School of Medicine is seeking a highly motivated Computational Biologist/ Postdoctoral Scholar to lead integrative epigenomics and transcriptomics analyses within a collaborative, data-rich research environment. Our group investigates how chromatin regulation, RNA biology, and metabolic signaling converge to control gene expression programs in cancer. The successful candidate will play a central role in analyzing and interpreting next-generation sequencing (NGS) datasets, including RNA-seq, ChIP-seq, ATAC-seq, eCLIP, TT-seq, Hi-C, and proteomics, to drive mechanistic discoveries and therapeutic insights.

Job Responsibility

  • Process, analyze, and integrate multi-omic data (RNA-seq, ChIP-seq, ATAC-seq, eCLIP, TT-seq, Hi-C, proteomics, metabolomics)
  • Perform quality control, alignment, differential expression/peak calling, and pathway enrichment analyses
  • Develop and maintain reproducible bioinformatics pipelines using R, Python, and/or shell scripting
  • Generate visualizations and statistical summaries to support figures and presentations
  • Curate, organize, and maintain large-scale datasets and metadata for ongoing projects
  • Work closely with wet-lab researchers to design experiments informed by computational results
  • Interface with sequencing, proteomics, metabolomics, and other cores to ensure data quality and compatibility
  • Document workflows and analyses for internal reports, publications, and grant submissions
  • Prepare analytical summaries, figures, and tables for manuscripts, talks, and grants
  • Present results in lab meetings and cross-disciplinary project meetings
  • Contribute to methods development, benchmarking, and implementation of new analytical tools

Requirements

  • Ph.D. (or equivalent, or near completion) in Bioinformatics, Computational Biology, Computer Science, Statistics, or a related quantitative field
  • Strong proficiency in R, Python, and UNIX/Linux command-line environments
  • Demonstrated experience analyzing NGS data (e.g., RNA-seq, ChIP-seq, or ATAC-seq)
  • Familiarity with common bioinformatics tools (e.g., STAR, Bowtie2, HISAT2, MACS2, DESeq2, edgeR, HOMER, BEDTools)
  • Solid understanding of statistics and data visualization for biological data

Nice to have

  • Experience with multi-omic data integration, single-cell RNA-seq, or chromatin conformation (Hi-C) data
  • Background in cancer biology, transcriptional regulation, or epigenetics
  • Familiarity with workflow management tools (e.g., Snakemake, Nextflow)
  • Experience with machine learning, dimensionality reduction, or network analysis
  • Excellent organizational and documentation skills with strong attention to detail
  • Ability to work both independently and collaboratively in a multidisciplinary research environment
  • Strong communication skills for explaining computational findings to experimental biologists
  • Enthusiasm for learning new analytical tools and approaches in a fast-paced research setting
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