Job DescriptionAs a member of the MSSM Scientific Computing Group, the Associate Computational Scientist works with scientists and researchers to effectively use MSSM HPC (high performance computing) clusters; assists in the research and deployment of codes on new technologies, and works with research groups to identify, implement and improve their computational and data workflow.
The Merad laboratory (Icahn School of Medicine at Mount Sinai) is looking for a highly motivated, detail-oriented individual to join our sequencing and imaging analysis team. The bioinformatics analyst is responsible for maintaining and contributing to our RNA sequencing (single cell and bulk RNA sequencing) and multiplex image data and code repositories.
Responsibilities- Contribute to setup, management and maintenance of sequencing and imaging data analysis pipelines.
- Manage sequencing and imaging data storage infrastructure.
- Adapt and optimize established internal and external coding workflows to process laboratory data.
- Curate, integrate and analyze internal and external sequencing and imaging data.
- Integrate with computational and biological team members to address needs of laboratory research.
- Work with the software engineering team to ensure pipeline upgrades and new pipelines are properly implemented in laboratory workflow.
- Assist collaborators with data access, analysis, and interpretation.
- Stay current on innovations in RNA sequencing and imaging analysis.
Qualifications- Masters degree or equivalent in a domain science; Ph.D. in a scientific domain preferred.
- Beginner level, with some experience in a scientific/academic computing environment or equivalent preferred.
Preferred Skills
- Masters degree or equivalent in a domain science; Ph.D. in a scientific domain preferred and in computational biology, bioinformatics, computer science, or similar.
- Strong scientific programming skills in R, Python, bash.
- Experience with pipeline development and management.
- Experience maintaining sequencing and imaging data and code infrastructure.
- Experience in batch HPC cluster environment with a parallel file system.
- Experience working in a Linux environment and scientific workflows.
- Attention to detail, documentation, organizational, and problem-solving skills
- Experience in an academic or research community environment.
- Team-oriented with excellent written and verbal communication skills.
- Experience benchmarking various analysis tools.
- Experience working with large datasets.
- Background in genomics and statistics.
- Experience analyzing single-cell RNA sequencing data and whole-slide histopathology images is a plus.
