Computational Biologist Job at jobRxiv

Computational Biologist

jobRxiv

Location:
United States

Category:
Research and Development

Contract Type:
Not provided

Salary:

61000.00 - 80000.00 USD / Year

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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

Additional Information:

Job Posted:
December 09, 2025

Employment Type:

Fulltime

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