Bioinformatician II- Tisch Cancer Center BiNGS Shared Resource
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 data analysis projects focused on cancer biology. BiNGS supports a broad range of genomic applications, develops bioinformatics tools, manages computational infrastructure, provides access to high-performance computing resources, and delivers computational training to the Mount Sinai research community. As a senior member of the team, the Bioinformatician will work 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 will lead multidisciplinary projects, work independently and collaboratively, and clearly communicate analyses to investigators from diverse scientific backgrounds. The position offers opportunities to work with cutting-edge sequencing technologies, collaborate on impactful research and publications, develop leadership skills, contribute to grant applications, and mentor trainees, including those from historically underrepresented backgrounds.
Requirements
- M.S. in Bioinformatics, Biomedical Informatics, Computational Biology, or Genomics; alternatively, an M.S. in a discipline requiring strong computational and analytical skills supplemented with some biology exposure. Candidates with a bachelor's degree and additional postgraduate experience are also considered.
- At least 2 years of postgraduate 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.
- Demonstrated ability to work independently and collaborate effectively in 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.
- Proven experience analyzing genomics and transcriptomics data, including WES, WGS, ULP WGS, bulk RNA-seq, and single-cell RNA-seq; candidates with a master's degree should have at least 2–3 years of experience.
- 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 through interpretation, visualization, manuscript contributions, and peer review.
- Manage multiple collaborative projects, including study design, project management, data analysis and interpretation, development of the scientific story, 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 emerging computational methods for multiomic data integration, visualization, and analysis.
- 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 and contribute to the growth and continued development of the BiNGS core and its services.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
