Postdoctoral Fellow-MSH-30001-337

Mount Sinai; United States; On-site; USD 65,000 - 80,000; Full time

Job summary

Mount Sinai seeks a Postdoctoral Fellow specializing in spatial and single-cell multi-omics to join a dynamic team. The Fellow will develop innovative assays and perform cutting-edge research in gene regulation and epigenomics.

This role offers the opportunity to lead projects, publish studies, and collaborate closely with scientists in a supportive environment. Candidates should have a Ph.D. and expertise in relevant genomic techniques.

Qualifications

• Ph.D. in Genomics, Molecular Biology, or related field.
• Strong interest in spatial and single-cell multi-omic technologies.
• Experience with next-generation sequencing library preparation.
• Proficiency in R, Python, or related programming languages.

Responsibilities

• Develop and benchmark spatial and single-cell multi-omic assays.
• Design experiments to improve assay robustness and sensitivity.
• Generate and analyze spatial and single-cell datasets.
• Integrate various omics datasets to study gene regulation.

Skills

Spatial and single-cell genomic methods

Computational analysis using R or Python

Problem-solving skills

Communication skills

Education

Ph.D. in Genomics or related field

Tools

Seurat

Scanpy

Cell Ranger

Job description

Job Title: Postdoctoral Fellow – Spatial and Single-Cell Multi-Omics

Introduction: We are seeking a highly motivated Postdoctoral Fellow to join our team and play a key role in developing, optimizing, and applying spatial and single-cell multi-omic technologies. The successful candidate will contribute to experimental method development, sequencing-based assay optimization, and associated computational analyses to study gene regulation, chromatin organization, and epigenomic mechanisms in complex biological systems.

We are looking for a candidate with strong interests in technology development, single-cell/spatial genomics, epigenomics, and integrative analysis. The Fellow will work closely with experimental and computational scientists in a highly collaborative environment and will have opportunities to lead independent projects, publish high-impact studies, and develop new tools for the broader research community.

Responsibilities

• Spatial and Single-Cell Method Development: Develop, optimize, and benchmark new spatial and single-cell multi-omic assays, including approaches that integrate transcriptomic, epigenomic, chromatin accessibility, DNA methylation, chromatin conformation, and/or protein-level measurements.
• Experimental Optimization and Troubleshooting: Design and perform experiments to improve assay sensitivity, throughput, robustness, and compatibility with primary tissues, low-input samples, and clinically relevant specimens. Optimize sample preparation, nuclei/cell isolation, library construction, sequencing strategies, and quality-control steps.
• Multi-Omic Data Generation and Analysis: Generate and analyze spatial and single-cell datasets (scRNA‑seq, scATAC‑seq, spatial transcriptomics, etc.), performing quality control, normalization, clustering, annotation, differential analysis, trajectory analysis, and regulatory feature identification.
• Data Integration: Integrate transcriptomic, epigenomic, spatial, and other omics datasets to investigate gene regulatory programs, cell‑state transitions, tissue organization, and disease‑associated molecular mechanisms.
• Pipeline and Tool Development: Develop, customize, and maintain computational pipelines for processing, analyzing, visualizing, and interpreting large‑scale single‑cell and spatial multi‑omic datasets. Ensure workflows are reproducible, scalable, and well documented.
• Validation and Benchmarking: Benchmark new methods against existing technologies using both experimental and computational metrics. Validate key biological findings through orthogonal genomic, molecular, imaging, or functional approaches.
• Collaboration and Communication: Work closely with lab members, collaborators, and core facilities to design experiments, analyze data, interpret results, and prepare manuscripts, grant applications, and presentations.
• Documentation and Dissemination: Maintain clear experimental records, analysis notebooks, protocols, and code documentation. Contribute to protocol sharing, software release, manuscript preparation, and presentation of research findings at scientific meetings.

Qualifications

• Ph.D. in Genomics, Molecular Biology, Epigenomics, Computational Biology, Bioinformatics, Biomedical Engineering, Computer Science, or a related field.
• Strong interest in developing and applying spatial and single-cell multi-omic technologies.
• Experience with single-cell or spatial genomic methods (scRNA‑seq, scATAC‑seq, CUT&Tag/CUT&RUN, DNA methylation profiling, Hi‑C, spatial transcriptomics, or related platforms).
• Experience with next‑generation sequencing library preparation, assay optimization, or molecular biology techniques (highly desirable).
• Proficiency in computational analysis using R, Python, or related programming languages.
• Familiarity with common single‑cell analysis frameworks and tools (Seurat, Scanpy, ArchR, Signac, Cell Ranger, Snakemake, Nextflow, etc.) is preferred.
• Strong problem‑solving skills and ability to troubleshoot experimental and computational workflows.
• Ability to work independently while also contributing effectively to collaborative projects.
• Excellent written and verbal communication skills.
• A strong publication record or demonstrated potential for independent scientific productivity.
• Preferred: Experience developing or optimizing new sequencing‑based technologies.
• Preferred: Experience working with primary tissues, low‑input samples, embryos, organoids, tumors, or clinically derived specimens.
• Preferred: Experience integrating multi‑omic datasets (transcriptomic, epigenomic, spatial, chromatin accessibility, DNA methylation, or chromatin conformation).
• Preferred: Familiarity with machine learning, statistical modeling, regulatory genomics, or gene regulatory network analysis.
• Preferred: Experience with high‑performance computing environments and reproducible workflow management.

Position Summary

The Postdoctoral Fellow will contribute to the development of innovative spatial and single-cell multi-omic technologies and apply these approaches to address important questions in gene regulation, epigenomics, development, and disease. The position offers an excellent opportunity to gain expertise at the interface of experimental technology development, computational genomics, and biological discovery.

Job Info

• Job Identification 3039566
• Job Category Professional
• Posting Date 06/24/2026, 04:19 PM
• Job Schedule Full time
• Job Shift Day
• Locations 1425 Madison Ave, New York, NY, 10029, US

Equal Opportunity Employer

The Mount Sinai Health System is an equal opportunity employer, complying with all applicable federal civil rights laws. We do not discriminate, exclude, or treat individuals differently based on race, color, national origin, age, religion, disability, sex, sexual orientation, gender, veteran status, or any other characteristic protected by law. We are deeply committed to fostering an environment where all faculty, staff, students, trainees, patients, visitors, and the communities we serve feel respected and supported. Our goal is to create a healthcare and learning institution that actively works to remove barriers, address challenges, and promote fairness in all aspects of our organization.