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Ideally undergraduate studies in a strongly quantitative discipline such as (e.g. physics, computer science, or maths). These skills could also have been developed, for example, through a PhD in computational biology, statistical genomics, or statistical genetics.
·Excellent knowledge and experience in one or more areas of human DNA analysis, such as rare disease genomics, family-based analysis, genetic association testing, risk score prediction, structural variation, pharmacogenomics, typing of complex genomic regions such as HLA/KIR
·Excellent knowledge in cancer genomics, approaches to call somatic variation and interpret cancer genomes.
·Strong knowledge of statistics and/or machine learning
·Strong knowledge of high throughput sequencing algorithms and available resources. Experience with full cycle of analysing NGS data from sequencing QC to annotation and prioritization of variants.
·Strong programming skills (Python, R)
Genomics Data Scientists work as part of squads building translating state of the art analytics into clinically-fit production quality solutions.
Genomics Data Scientists investigate and develop solutions to extract more information from the genome (alignment and variant calling) and to interpret the genome in the context of a persons clinical features