Postdoctoral Fellow-MSH-30025-250

The Izzo Lab (Laboratory of Clonal Evolution and Molecular Epigenetics of Cancer) at the Icahn School of Medicine at Mount Sinai is seeking a highly motivated Postdoctoral Fellow in Bioinformatics to join our team. Our research focuses on uncovering the fundamental mechanisms driving the onset, therapy resistance, and progression of hematological malignancies, with a particular emphasis on clonal evolution,genetic heterogeneity, and epigenetic plasticity. We develop and apply cutting-edge single-cell sequencing technologies (including multi-omic approaches integrating genomics, transcriptomics, and epigenomics) to directly profile patient samples. This work aims to map genotype-to-phenotype relationships, understand how somatic mutations drive epigenetic deregulation, and identify vulnerabilities that can be targeted to overcome therapy resistance and improve patient outcomes. The successful candidate will play a central role in the computational analysis of large-scale single-cell datasets from ongoing projects in blood cancers (e.g., myeloproliferative neoplasms, MDS, and leukemia). This is an outstanding opportunity for a computational scientist interested in translational cancer research within a dynamic, collaborative, and highly supportive environment at the Tisch Cancer Institute and Center for Advancement of Blood Cancer Therapies (CABCT).

• Ph.D. (or M.D./Ph.D.) in Bioinformatics, Computational Biology, Genomics, Biostatistics, or a closely related field.
• Strong expertise in single-cell sequencing analysis, with demonstrated experience in R/Bioconductor and/or Python (e.g., Seurat, Scanpy, ArchR, Signac, or similar tools).
• Proficiency in handling large-scale genomic datasets, statistical modeling, machine learning (optional but a plus), and high-performance computing (e.g., SLURM clusters).
• Familiarity with cancer biology, epigenetics, or clonal evolution is highly desirable.
• Excellent communication skills, ability to work independently and in teams, and a track record of peer-reviewed publications.
• Prior experience with hematological malignancies or multi-omic integration is a strong advantage.

What We Offer

• Competitive salary and benefits, commensurate with experience and NIH guidelines (including subsidized housing options in New York City).
• Access to state-of-the-art computational resources and core facilities at Mount Sinai.
• Mentorship from Dr. Franco Izzo and close collaboration with leading investigators in oncology, single-cell genomics, and hematology.
• Opportunities for career development, including independent projects, grant applications (e.g., K99/R00), and networking within the vibrant Mount Sinai research community.
• A creative, rigorous, and supportive lab culture focused on high-impact science with translational potential.

How to Apply

Interested candidates should send the following to

franco.izzo@mssm.edu (mailto: franco.izzo@mssm.edu)(with the subject line ?Postdoc Bioinformatics Application ? Your Last Name?):

• Cover letter describing research interests, relevant experience, and career goals.
• Curriculum vitae (CV).
• Contact information for 2?3 references.
• One representative publication (PDF).

Applications will be reviewed on a rolling basis until the position is filled. Mount Sinai is an equal opportunity employer; we encourage applications from diverse backgrounds.

• SPOC-UAW Local 4100 at Icahn School of Medicine (Post Docs), 824 - Oncological Sciences

• ISM, Icahn School of Medicine

• Perform advanced bioinformatics analysis of single-cell multi-omic data (scRNA-seq, scATAC-seq, multiome, CITE-seq, and emerging spatial/single-cell technologies), including quality control, integration, clustering, trajectory inference, and differential analysis.

• Develop and apply custom computational methods or pipelines to study genetic heterogeneity, clonal evolution, somatic mutation effects, and epigenetic regulation (e.g., chromatin accessibility, gene regulatory networks, and plasticity).

• Integrate multi-modal datasets with clinical and functional data to generate biological insights and hypotheses.

• Collaborate closely with wet-lab team members on experimental design, data interpretation, and validation.

• Contribute to manuscript preparation, grant writing, and presentation of findings at conferences.

• Mentor junior lab members and participate in lab meetings and journal clubs.