About the Role
The position involves leading computational research efforts to analyze large-scale genomic datasets, develop novel analytical approaches, and contribute to understanding the molecular basis of cancer progression and treatment response.
Responsibilities
- Lead the design and execution of computational analyses on cancer genomics data
- Develop and apply algorithms for detecting tumor heterogeneity and clonal evolution
- Integrate multi-omics datasets including whole-genome, transcriptome, and epigenetic data
- Collaborate with experimental biologists to interpret genomic findings
- Mentor junior computational scientists and cross-functional team members
- Contribute to grant writing and scientific manuscript preparation
- Stay current with advances in computational biology and cancer genomics
- Optimize data pipelines for scalability and reproducibility
- Ensure data quality and statistical rigor across projects
- Present findings at scientific meetings and internal seminars
- Drive innovation in single-cell sequencing data analysis
- Support clinical translation of computational discoveries
- Work closely with bioinformatics and biostatistics teams
- Manage computational resources and cloud-based platforms
- Implement best practices for data sharing and version control
- Contribute to the development of open-source software tools
- Evaluate emerging technologies for genomic data generation
- Participate in interdisciplinary project teams
- Maintain documentation for analytical methods and workflows
- Ensure compliance with data privacy and security standards
- Lead project planning and timeline estimation for computational tasks
- Foster collaborations across research groups
- Translate biological questions into computational frameworks
- Validate computational predictions with experimental follow-up
- Promote reproducible research practices across the team
Compensation
Competitive salary and comprehensive benefits package
Work Arrangement
Hybrid work model with on-site and remote options
Team
Collaborative research environment within a multidisciplinary cancer research team
About the Shah Lab
The Shah Lab focuses on understanding the genetic and epigenetic mechanisms driving cancer progression, with an emphasis on tumor heterogeneity and clonal evolution. Research integrates computational modeling with experimental validation to uncover drivers of therapeutic resistance and metastasis.
Why Join Us?
Opportunity to lead high-impact research in a world-renowned cancer center. Access to cutting-edge genomic technologies, large patient cohorts, and a collaborative network of clinicians and scientists. Support for independent grant applications and leadership development.
Visa sponsorship available for qualified international candidates
