Computational Biologist / Postdoc in Epigenomics and Transcriptomics

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.

Working closely with experimental biologists and computational collaborators, the postdoctoral scholar will develop and apply analytical pipelines, integrate multi-omic datasets, and contribute to conceptual models of transcriptional regulation and nucleolar biology. This position provides the opportunity to contribute to high-impact manuscripts, collaborative grants, and emerging intellectual property. The Lauberth Lab offers a dynamic and interdisciplinary environment with strong mentorship, access to cutting-edge technologies, and the opportunity to shape projects at the interface of chromatin biology, RNA regulation, and cancer metabolism.

Key Responsibilities

Data Processing and Analysis

• 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.

Data Management and Collaboration

• 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.

Scientific Communication and Methods Development

• 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.

Minimum Qualifications

• 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.

Preferred Qualifications

• 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.

Desired Skills and Attributes

• 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.

Application Instructions

Interested candidates should submit a single PDF via JobRxiv (and/or by email to [Please click the Apply button for the link or address]) that includes:

• Cover letter describing relevant experience, research interests, and motivation for applying.
• Curriculum vitae (CV).
• Names and contact information for 2–3 references (letters may be requested at a later stage).

Applications will be reviewed on a rolling basis until the position is filled.

Tagged as: Life Sciences