Assistant Scientist (Computational Biology) – Mzoughi lab – Oncoplasticity

Mount Sinai Health System • New York, NY

6d

About The Position

The Mzoughi Lab Our lab focuses on understanding the epigenetic mechanisms driving phenotypic heterogeneity and plasticity in cancer. Using cutting-edge multiomics technologies and lineage tracing, we ONCOPLASTICITY Mzoughi lab explore how tumor cells evolve and adapt during disease progression and under therapeutic pressures. We are seeking a highly motivated Post-Doctoral Researcher/Scientist with a strong computational biology background to join our team. The successful candidate will apply and develop computational tools to analyze large-scale omics datasets, including bulk and single-cell RNA-seq, ATAC-seq, and CUT&Tag, and will contribute to studies elucidating tumor plasticity mechanisms. Experience in lineage tracing and single-cell data analysis is strongly preferred.

Requirements

• PhD in Biological Sciences or related field
• Two years experience

Nice To Haves

• Proficiency in programming languages such as R and Python, with demonstrated experience in analyzing high-dimensional biological datasets.
• Experience with computational tools and packages for multiomics data analysis (e.g., Seurat, Monocle, edgeR, DESeq2, ArchR).
• Familiarity with lineage tracing analysis methods and software is highly desirable.
• Strong skills in statistical modeling, data visualization, and interpretation of biological findings
• Familiarity with high-performance computing environments and version control systems (e.g., Git).
• Experience in analyzing single-cell epigenomics and transcriptomics datasets (e.g., single-cell RNA-seq and ATAC-seq).
• Knowledge of machine learning techniques for biological data analysis.
• Strong publication record in peer-reviewed journals.

Responsibilities

• Analyze bulk and single-cell RNA-seq, ATAC-seq, and CUT&Tag datasets.
• Develop and optimize pipelines for integrating and interpreting multiomics data.
• Collaborate with both wet-lab and other dry-lab team members to generate hypotheses and refine experimental designs.
• Analyze lineage tracing datasets to uncover dynamic cellular transitions and clonal evolution.
• Present findings in lab meetings, conferences, and manuscripts.

What This Job Offers

• Education Level: Ph.D. or professional degree
• Number of Employees: 5,001-10,000 employees