Cancer Vaccine Jobs (NOW HIRING)

The Computational Scientist I will develop and maintain scalable, modular bioinformatics pipelines for antigen discovery and prioritization, and integrative analysis of genomic (e.g., WES/WGS), transcriptomic (e.g., RNA-seq), and proteomic (e.g., mass spectrometry) data. The role focuses on building reproducible, end-to-end computational workflows for processing, analyzing, and interpreting high-throughput multi-omic datasets in a cancer immunogenomics setting.

The role will contribute to development of computational platforms supporting translational cancer immunotherapy research, with applications in clinical trial settings for the design of personalized and shared (off-the-shelf) vaccine strategies.

The candidate will join a multidisciplinary team with extensive experience in computational immunogenomics and translational cancer research. The group has developed and applied the OpenVax platform in support of multiple clinical trial efforts focused on cancer vaccine strategies. Working closely with this team, the Computational Scientist will contribute to extending existing capabilities, introducing new computational functionality, and advancing the development of next-generation analytical workflows and platforms.

The position involves working with next-generation sequencing and proteomic datasets to perform data processing, quality control, and integrative analysis. The individual will design, implement, and maintain modular pipeline components across data processing, analysis, and reporting layers, ensuring scalability, reproducibility, and portability across computational environments.

Strength through Unity and Inclusion

The Mount Sinai Health System is committed to fostering an environment where everyone can contribute to excellence. We share a common dedication to delivering outstanding patient care. When you join us, you become part of Mount Sinai's unparalleled legacy of achievement, education, and innovation as we work together to transform healthcare. We encourage all team members to actively participate in creating a culture that ensures fair access to opportunities, promotes inclusive practices, and supports the success of every individual.

At Mount Sinai, our leaders are committed to fostering a workplace where all employees feel valued, respected, and empowered to grow. We strive to create an environment where collaboration, fairness, and continuous learning drive positive change, improving the well-being of our staff, patients, and organization. Our leaders are expected to challenge outdated practices, promote a culture of respect, and work toward meaningful improvements that enhance patient care and workplace experiences. We are dedicated to building a supportive and welcoming environment where everyone has the opportunity to thrive and advance professionally. Explore this opportunity and be part of the next chapter in our history.

About the Mount Sinai Health System:

Mount Sinai Health System is one of the largest academic medical systems in the New York metro area, with more than 48,000 employees working across eight hospitals, more than 400 outpatient practices, more than 300 labs, a school of nursing, and a leading school of medicine and graduate education. Mount Sinai advances health for all people, everywhere, by taking on the most complex health care challenges of our time - discovering and applying new scientific learning and knowledge; developing safer, more effective treatments; educating the next generation of medical leaders and innovators; and supporting local communities by delivering high-quality care to all who need it. Through the integration of its hospitals, labs, and schools, Mount Sinai offers comprehensive health care solutions from birth through geriatrics, leveraging innovative approaches such as artificial intelligence and informatics while keeping patients' medical and emotional needs at the center of all treatment. The Health System includes more than 9,000 primary and specialty care physicians; 13 joint-venture outpatient surgery centers throughout the five boroughs of New York City, Westchester, Long Island, and Florida; and more than 30 affiliated community health centers. We are consistently ranked by U.S. News & World Report's Best Hospitals, receiving high "Honor Roll" status, and are highly ranked: No. 1 in Geriatrics, top 5 in Cardiology/Heart Surgery, and top 20 in Diabetes/Endocrinology, Gastroenterology/GI Surgery, Neurology/Neurosurgery, Orthopedics, Pulmonology/Lung Surgery, Rehabilitation, and Urology. New York Eye and Ear Infirmary of Mount Sinai is ranked No. 12 in Ophthalmology. U.S. News & World Report's "Best Children's Hospitals" ranks Mount Sinai Kravis Children's Hospital among the country's best in several pediatric specialties. The Icahn School of Medicine at Mount Sinai is ranked No. 11 nationwide in National Institutes of Health funding and in the 99th percentile in research dollars per investigator according to the Association of American Medical Colleges. Newsweek's "The World's Best Smart Hospitals" ranks The Mount Sinai Hospital as No. 1 in New York and in the top five globally, and Mount Sinai Morningside in the top 20 globally.

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.

• Masters degree or equivalent in a domain science; Ph.D in a scientific domain preferred.
• 3 years, preferably in a scientific/academic computing environment or equivalent experience.
• Preferred qualifications:
  • Strong proficiency in Python for scientific computing and pipeline development, with an emphasis on software engineering best practices (e.g., code structure, version control, testing, and documentation) 
  • Experience developing, maintaining, or extending bioinformatics pipelines or computational workflows 
  • Experience working with next-generation sequencing (NGS) data (e.g., RNA-seq, WES/WGS), including data processing and quality control 
  • Familiarity with genomic and transcriptomic data analysis concepts 
  • Experience working with large-scale datasets in high-performance computing (HPC) or cloud-based environments 
  • Familiarity with containerization and reproducible workflows (e.g., Docker, Singularity) is preferred 
  • Experience with workflow management systems (e.g., Nextflow, Snakemake) is a plus
  • Exposure to proteomic data (e.g., mass spectrometry) and/or multi-omic data integration is a plus 
  • Experience with data visualization and generation of structured outputs for scientific interpretation is a plus 
  • Familiarity with cancer genomics or immunogenomics
  • Ability to work independently on defined tasks and collaboratively within a multidisciplinary team 
  • Strong communication skills, with the ability to clearly present computational results to scientific collaborators 
  • Strong organizational skills and attention to detail

• Masters degree or equivalent in a domain science; Ph.D in a scientific domain preferred.
• 3 years, preferably in a scientific/academic computing environment or equivalent experience.
• Preferred qualifications:
  • Strong proficiency in Python for scientific computing and pipeline development, with an emphasis on software engineering best practices (e.g., code structure, version control, testing, and documentation) 
  • Experience developing, maintaining, or extending bioinformatics pipelines or computational workflows 
  • Experience working with next-generation sequencing (NGS) data (e.g., RNA-seq, WES/WGS), including data processing and quality control 
  • Familiarity with genomic and transcriptomic data analysis concepts 
  • Experience working with large-scale datasets in high-performance computing (HPC) or cloud-based environments 
  • Familiarity with containerization and reproducible workflows (e.g., Docker, Singularity) is preferred 
  • Experience with workflow management systems (e.g., Nextflow, Snakemake) is a plus
  • Exposure to proteomic data (e.g., mass spectrometry) and/or multi-omic data integration is a plus 
  • Experience with data visualization and generation of structured outputs for scientific interpretation is a plus 
  • Familiarity with cancer genomics or immunogenomics
  • Ability to work independently on defined tasks and collaboratively within a multidisciplinary team 
  • Strong communication skills, with the ability to clearly present computational results to scientific collaborators 
  • Strong organizational skills and attention to detail

Compensation Statement

The Mount Sinai Health System (MSHS) provides salary ranges that comply with the New York City Law on Salary Transparency in Job Advertisements. The salary range for the role is $96,461.00 - $165,465.29 Annually. Actual salaries depend on a variety of factors, including experience, education, and operational need. The salary range or contractual rate listed does not include bonuses/incentive, differential pay or other forms of compensation or benefits.

, 031 - Hematology & Medical Oncology - ISM, Icahn School of Medicine

• Develop, implement, and maintain scalable bioinformatics pipelines for genomic, transcriptomic, and proteomic data analysis 
• Design modular components for end-to-end workflows, including data ingestion, preprocessing, analysis, and reporting 
• Integrate multi-omic datasets to support antigen discovery and prioritization 
• Perform data processing, quality control, and validation of high-throughput sequencing and proteomic datasets 
• Benchmark, optimize, and validate computational methods and workflows 
• Package and deploy pipelines in reproducible environments (e.g., Docker, Singularity) and support execution on HPC systems 
• Manage and analyze large-scale datasets in HPC environments 
• Generate structured outputs, visualizations, and reports for downstream biological interpretation 
• Collaborate with computational, experimental, and clinical teams to translate analytical results into translational insights 
• Contribute to scientific reports, presentations, and manuscripts 
• Stay current with emerging computational methods in genomics and immunogenomics 
• Perform other related duties as assigned