Bioinformatician II- Tisch Cancer Center BiNGS Shared Resource

Mount Sinai Health System • New York, NY

5d

About The Position

The Bioinformatics for Next Generation Sequencing (BiNGS) Shared Resource at the Tisch Cancer Center, Icahn School of Medicine at Mount Sinai, is seeking an experienced Bioinformatician II to lead transcriptomics, epigenomics, and multiomics data analysis projects focused on cancer biology. BiNGS supports investigators with next-generation sequencing analysis, computational tools, training, and bioinformatics expertise across applications including bulk and single-cell sequencing, spatial transcriptomics, DNA methylation, whole-genome and whole-exome sequencing, and emerging long-read technologies. The resource also develops bioinformatics tools, manages computational infrastructure, provides access to high-performance computing, and delivers computational training.

As a senior member of the team, the Bioinformatician 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. The successful candidate is expected to lead multidisciplinary projects and clearly communicate complex analyses to investigators with diverse scientific backgrounds.

Projects may involve cancer progression, histone variants and enhancer analysis, chromatin accessibility, transcription factor networks, integration of bulk and single-cell datasets, and long-read sequencing to study chromatin architecture. The role offers opportunities to work with cutting-edge sequencing technologies, contribute to impactful cancer research and publications, develop leadership skills, and support an inclusive scientific environment through mentorship.

Requirements

• M.S. in Bioinformatics, Biomedical Informatics, Computational Biology, Genomics, or a discipline requiring strong computational and analytical skills supplemented with biology exposure; candidates with a bachelor's degree and additional post-graduate experience are also considered.
• 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 in programming environments such as MATLAB, R, Bioconductor, Perl, and C++.
• Strong programming skills in Python, R, Linux, and Bash.
• Excellent analytical, organizational, communication, and problem-solving skills.
• Ability to work independently and collaborate effectively within multidisciplinary research teams.

Nice To Haves

• Ph.D. in a related field.
• Master's degree or Ph.D. in Bioinformatics, Computational Biology, Computer Science, or a related quantitative discipline.
• For candidates with a master's degree, 2–3 years of experience.
• Proven experience analyzing genomics and transcriptomics data, including WES, WGS, ULP WGS, bulk RNA-seq, and single-cell RNA-seq.
• Experience with genomics software such as Bowtie2, BWA, GATK, ANNOVAR, CNVKit, STAR, Cell Ranger, Seurat, Slingshot, Monocle 3, Salmon, and DESeq2.
• Experience 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, story development, and presentation of results to investigators.
• Integrate internally generated datasets with public resources such as COSMIC, TCGA, and GEO to identify 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.
• Perform 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 trainees from historically underrepresented backgrounds.
• Contribute to the continued growth and services of the BiNGS core.

Benefits

• Access to Mount Sinai high-performance computing infrastructure and cloud computing platforms.
• Opportunities to contribute to high-impact manuscripts and grant applications.
• Opportunities to mentor junior scientists and develop leadership skills.
• Opportunity to collaborate with recognized investigators and work on cutting-edge cancer genomics and multiomics projects.

What This Job Offers

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