Senior & Staff Bioinformatics Scientist's

18 ott - Vercelli
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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