Scientist Computational Biology
hace 1 semana
**Responsibilities**
- Perform bioinformatics analyses of single-cell RNA-Seq data generated from clinical and pre-clinical samples.
- Perform multi-modal (multi-omic) genomics analyses that require the integration of multiple types of single-cell genomics and spatial omics data or the integration of single-cell and bulk genomics data.
- Work closely with the CSCS lab team to evaluate internally-generated single-cell genomics data.
- Support the design of novel experimental strategies for single-cell genomics data generation from a variety of clinical sample types.
- Develop analytical methods and pipelines for routine internal usage and evaluate publicly-available analytical tools.
- Routinely share results with a diverse group of molecular & cell biologists, bioinformaticians, and clinical leads.
**Qualifications**
- Relevant MS or BS (minimum of 2 years of experience):
- Background in bioinformatics, computational biology, systems biology, biostatistics, data science or related discipline.
- Technical expertise with handling next generation sequencing (NGS) data with an emphasis on transcriptomic analyses. Direct experience with single-cell RNA-Seq (scRNA-Seq) or spatial transcriptomics data is a plus. Experience with multi-modal data analyses (e.g. RNA-Seq and ATAC-Seq) is also a plus.
- Working experience leveraging genomic data to study cell biology. Direct experience with cancer-focused genomic analyses is a plus.
- Fluency with R and/or Python programming.
- Experience with Unix and shell scripting, code documentation and version control.
- Experience with high-performance computing (HPC) and HPC schedulers is a plus.
- Deep understanding of cancer cell and molecular biology required. Understanding of immunology is a plus.
- Deep understanding of genomics and NGS data generation required.
- Skilled at sharing analyses of complex data types to non-experts. Experience with producing analytical reports for distribution to non-programmers.
- Experience working in a cross-disciplinary scientific environment that requires extensive interaction with lab scientists. Prior experience directly performing cell or molecular biology lab work is a plus.
- Excellent organizational skills and capacity to lead multiple projects required.
- Ability to efficiently alternate between independent work and team-based science, requiring direct support of other team members.
**Desirable Qualifications**
- Experience performing single-cell RNA-Seq or spatial transcriptomics data analysis in an industry setting is a plus.
- Advanced background in machine learning, artificial-intelligence, Bayesian statistics or other non-traditional approaches to biological data analysis is a plus.
- Demonstrated track record of performance involving the successful completion of projects. Publications in peer-reviewed journals, conference presentations, and public code repositories are a plus.
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