18 ott - Italia
Illumina
Overview
In this role you will help advance genomic analysis at scale by designing novel algorithms and building production-ready software for the DRAGEN platform and ICA integration. You will join a cross-functional team of scientists, engineers, and clinicians to turn complex sequencing data into actionable insights. The work spans rare disease, oncology, population genomics, and precision medicine, with a strong emphasis on impactful, real-world applications. This is a mission-driven opportunity to shape genomic technologies that improve lives through collaboration and rigorous scientific development.
Retribuzione / Benefits
- premio or commission eligibility
- equity potential
- flexible time off
- summer shutdown
- pension contributions (UK)
- private medical insurance (UK)
Responsabilità
- Design and implement computational methods for genomic data analysis
- Develop high-performance production software with emphasis on speed and accuracy
- Interpret complex sequencing data to support product/workflow development
- Collaborate with software, FPGA, quality, clinical genomics, and product teams
- Advance DRAGEN platform across germline, somatic, DNA, RNA, SV, CNV,
and targeted sequencing applications
- Engage with customers and researchers to understand emerging needs
- Present findings to specialist and non-specialist audiences
- Contribute to publications, documentation, and thought leadership
- Evaluate emerging technologies to improve performance and outcomes
- Foster collaboration, accountability, and innovation across teams
Requisiti fondamentali
- Master's or PhD in Bioinformatics, Computer Science, Statistics, Engineering, or related discipline
- Strong experience developing bioinformatics methods for NGS data
- Expertise in secondary analysis workflows (mapping, alignment, variant calling, genomic interpretation)
- Proficiency in C/C++ or equivalent high-performance languages
- Experience with large-scale genomic datasets and production software environments
- Knowledge of cancer genomics, rare disease analysis, population genetics, transcriptomics, or multi-omics
- curiosity
- innovation
- ability to collaborate across disciplines
- bioinformatics methods for NGS
- algorithm development
- secondary analysis workflows
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