Computational Biologist / Postdoc in Epigenomics and Transcriptomics
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.
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.
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
Get Similar Jobs in Your Inbox
Weekly digest of top bioinformatics jobs. No spam.
Job Information
Get Similar Jobs by Email
Weekly digest of Northwestern University Feinberg School of Medicine and similar companies. Free.
