Job:Bioinformatics Scientist 1 @ Illumina – Oncology & multi-omics - UK based
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6 weeks ago

We are seeking a data analyst to be a part of Medical Genomics Research team at Illumina to help analyse clinical samples from external collaborations, to define best practice and to participate in developing innovative methods that transform sequencing results into discoveries and clinical insights that may improve patient care.

The Medical Genomics Research Informatics group prototypes tools to analyse sequencing data from Illumina’s instruments, particularly in oncology and rare disease, through collaborative projects such as UK’s Genomics England 100,000 genomes project and the Personalised Breast Cancer Program.

Your responsibilities may include:

  • Applying best practice statistical and bioinformatics methods to combine the analysis of cancer genomes and transcriptomes (gene expression signatures, germline and somatic mutations, other biomarkers)
  • Developing and improving prototypes for clinical reports and biomarker detection
  • Developing analytical bioinformatics tools to drive the development of whole-transcriptome and whole-genome oncology clinical tests
  • Supporting the sequencing team with experimental design and data analysis to ensure the success of our collaborations

Preferred background, skills, and experience:

  • Ph.D. or equivalent in Bioinformatics, Computational Biology or related field

  • Experience in sequencing data analysis, ideally RNA-Seq, and open-source bioinformatics tools

  • Expert in either R or Python, comfortable with shell scripting and HPC, familiarity with git

  • Good understanding of applied statistics

  • Excellent written and verbal communication skills

  • Ability to contribute independently and collaboratively, take ownership of assigned tasks, and excel in a fast-paced environment

Candidates who have a background in oncology or experience analysing clinical samples would be advantaged

More information can be found here: link

biomarkers R bioinformatics cancer RNA-Seq • 233 views
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