Postdoctoral Fellow, Transcription Regulation using Genomics and Machine Learning

Biohub • New York, NY

7d • Onsite

About The Position

Biohub is seeking a Postdoctoral Fellow to investigate how transcription factors regulate gene expression programs in cancer and how disease-associated mutations in transcription factors disrupt these programs to drive malignant phenotypes. This project aims to define the molecular functions of transcription factors in normal and diseased states, map how mutations alter chromatin and transcriptional regulation, and utilize machine learning to predict and test novel mutant-TF-specific functions. The role involves defining transcription factor mechanisms, analyzing mutation-driven regulation, applying AI/ML for functional discovery, optimizing genomic library preparation, performing molecular and cell biology validation, and integrating pathways for disease modeling.

Requirements

• PhD in Molecular Biology, Cancer Biology, Genetics, Genomics, or a related field.
• Strong hands-on experience in genomic library preparation, particularly for chromatin and transcription-focused assays such as GRO-seq/PRO-seq, CUT&RUN, ATAC-seq, DNA methylation profiling.
• Expertise in basic molecular biology techniques, mammalian cell culture, engineered cell models, and/or primary samples.
• Experience with functional perturbation methods such as CRISPR editing, CRISPR screening, or other genetic manipulation approaches.
• Demonstrated work and publication in transcription factor biology, gene regulation, epigenomics, or cancer mechanisms, reflecting independent experimental work and mechanistic biological insight.

Nice To Haves

• Familiarity with computational biology methods and genomic data analyses.
• Experience studying transcription factors, chromatin regulators, or gene regulatory mechanisms in cancer or other disease contexts.
• Familiarity with comparing wild-type and mutant protein function using genomic and molecular assays.
• Interest in collaborative, interdisciplinary research at the interface of transcription, epigenetics, and disease biology.

Responsibilities

• Define how transcription factors control gene expression, chromatin accessibility, and regulatory element activity in cancer-relevant cellular contexts.
• Map transcription factor occupancy, chromatin state, and nascent transcription using GRO-seq/ PRO-seq, CUT&RUN, ATAC-seq, DNA methylation profiling.
• Integrate transcription factor binding data with enhancer activity, promoter usage, and transcriptional outputs to identify direct regulatory targets and core gene networks.
• Apply CRISPR editing to test candidate genes, regulatory elements, and pathways.
• Determine how cancer-associated mutations in transcription factors alter DNA binding, cofactor recruitment, chromatin remodeling, and transcriptional control.
• Compare wild-type and mutant transcription factor function across genomic, epigenomic, and transcriptional assays to identify mutation-specific regulatory defects.
• Characterize the mutated-TF-associated co-factors, transcription factor, chromatin remodeling through protein-protein interactions.
• Dissect how these changes impact oncogenic pathways, lineage identity, cellular plasticity, and disease progression.
• Collaborate closely with AI/ML scientists to apply protein language models and related computational approaches to transcription factors and their disease-associated variants.
• Use these models to predict potential novel molecular functions, protein-protein interaction partners, and mutation-associated cellular phenotypes.
• Design and execute experimental strategies to test model-derived predictions in laboratory settings, using genomic, molecular, and functional assays to validate predicted mechanisms and disease-relevant consequences.
• Help establish an iterative framework in which computational predictions inform experiments, and experimental results refine downstream modeling and hypothesis generation.
• Lead and optimize genomic library preparation workflows for chromatin and transcription-focused assays, with strong emphasis on GRO-seq/PRO-seq, CUT&RUN, ATAC-seq, DNA methylation assays, and RNA-seq.
• Generate high-quality sequencing libraries from cell lines, engineered models, and primary samples, ensuring rigorous experimental design, QC, and reproducibility.
• Support comparative profiling across perturbation conditions, mutant backgrounds, and treatment states to reveal context-specific transcription factor biology.
• Perform core molecular biology methods, including tissue culture, organoid and patient sample processing, ChIP, gel electrophoresis, cloning, FACS, and ELISA etc., to validate mechanistic hypotheses.
• Use genome engineering and perturbation approaches, including CRISPR-based editing and CRISPR screening, to test the functional consequences of transcription factor mutations and candidate regulatory dependencies.
• Validate key findings through orthogonal assays in relevant cellular models.
• Identify critical downstream effectors, co-factors, and candidate therapeutic vulnerabilities emerging from mutant transcription factor activity.
• Contribute to the development of mechanistic frameworks explaining how transcription factor dysfunction gives rise to disease.

Benefits

• Generous employer match on employee 401(k) contributions
• Paid time off to volunteer
• Funding for select family-forming benefits
• Relocation support

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree