Bioinformatician II- Tisch Cancer Center BiNGS Shared Resource

Mount Sinai Health System • New York, NY

6d

About The Position

The Bioinformatics for Next Generation Sequencing (BiNGS) Shared Resource at the Tisch Cancer Center, Icahn School of Medicine at Mount Sinai, seeks an experienced Bioinformatician II to lead transcriptomics, epigenomics, and multiomics analyses focused on cancer biology. BiNGS supports a broad range of genomic applications, develops bioinformatics tools, manages computational infrastructure and high-performance computing resources, and provides computational training to the Mount Sinai research community.

As a senior member of the team, the Bioinformatician II will collaborate with investigators across the Tisch Cancer Center and Mount Sinai to design, execute, interpret, and communicate complex genomic analyses. The role leads collaborative projects from inception through publication, mentors junior bioinformaticians, and contributes to the growth of the core and its services. Projects may involve cancer genomics, chromatin biology, bulk and single-cell sequencing, spatial genomics, multiomics, and emerging sequencing technologies. The successful candidate will lead multidisciplinary work, communicate complex analyses to investigators with diverse backgrounds, and contribute to publications, grant applications, and an inclusive scientific environment.

Requirements

• At least 2 years of post-graduate experience in a research environment, including manipulation of large biological datasets.
• Advanced knowledge of genetics and/or statistical analysis software and online resources.
• Experience with programming environments such as MATLAB, R, Bioconductor, Perl, and C++.
• Strong analytical, organizational, communication, and problem-solving skills.
• Ability to work independently and collaborate effectively within multidisciplinary research teams.
• Scientific curiosity and attention to detail.

Nice To Haves

• Master's or Ph.D. in Bioinformatics, Computational Biology, Computer Science, or a related quantitative discipline; a Ph.D. in a related field is preferred.
• For candidates with a master's degree, 2–3 years of experience analyzing genomics and transcriptomics data.
• Experience analyzing genomics and transcriptomics data, including WES, WGS, ULP WGS, and bulk and single-cell RNA-seq.
• Strong programming skills in Python, R, Linux, and Bash.
• Experience with genomics software such as Bowtie2, BWA, GATK, ANNOVAR, CNVKit, STAR, Cell Ranger, Seurat, Slingshot, Monocle3, Salmon, and DESeq2.
• Experience working in Linux-based high-performance computing environments with parallel file systems.
• Experience managing analyses and data using AWS or comparable cloud computing platforms.
• Experience with AI-assisted software development tools such as Claude Code or GitHub Copilot for software development, debugging, and workflow optimization.
• Strong understanding of chromatin biology, transcriptional regulation, and next-generation sequencing technologies.

Responsibilities

• Provide scientific and analytical leadership for complex genomics and transcriptomics projects, translating investigator questions into rigorous computational strategies and leading analyses, interpretation, visualization, and manuscript contributions through publication and peer review.
• Manage multiple collaborative projects, including study design, project management, data analysis and interpretation, development of scientific narratives, and presentation of results to investigators.
• Integrate internally generated datasets with public resources such as COSMIC, TCGA, and GEO to identify biologically meaningful patterns and generate hypotheses.
• Develop publication-quality figures, visualizations, and analytical reports for manuscripts, grant applications, and scientific presentations.
• Evaluate, implement, and benchmark computational methods for multiomic data integration, visualization, and analysis, including approaches such as MOFA and Similarity Network Fusion.
• Conduct large-scale analyses using the Mount Sinai HPC environment and oversee data management, storage, archiving, and workflow execution.
• Maintain and support cloud-based computational resources, preferably using AWS, including deployment of interactive reports and web-based applications.
• Mentor junior bioinformaticians and trainees, including those from historically underrepresented backgrounds.
• Contribute to the continued growth and services of the BiNGS core.
• Work on multidisciplinary cancer research projects involving applications such as ULP WGS, bulk and single-cell transcriptomics and epigenetics, enhancer analysis, chromatin accessibility, transcription-factor networks, mutant p53, and long-read sequencing.

Benefits

• Opportunity to work on cutting-edge cancer genomics and multiomics projects using current sequencing technologies.
• Collaboration with investigators across the Tisch Cancer Center and the broader Mount Sinai research community.
• Opportunity to lead impactful projects from study design through publication.
• Opportunities to contribute to manuscripts, grant applications, and computational methodologies.
• Access to Mount Sinai HPC infrastructure and cloud computing platforms.
• Opportunity to mentor junior scientists and help shape the direction of a growing bioinformatics core.
• Opportunity to expand expertise in transcriptomics, epigenomics, chromatin biology, spatial genomics, and emerging sequencing technologies.
• Opportunity to develop leadership skills and contribute to an inclusive scientific environment.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level