Computational Scientist - Hematology & Medical Oncology

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.

• 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
   

• 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