Computational and/or Experimental Hybrid Scientist – Foster City, CA (SF Bay Area)

What if the work you did every day could impact the lives of people you know? Or all of humanity? At Illumina, we are expanding access to genomic technology to realize health equity for billions of people around the world. Our efforts enable life-changing discoveries that are transforming human health through the early detection and diagnosis of diseases and new treatment options for patients. Working at Illumina means being part of something bigger than yourself. Every person, in every role, has the opportunity to make a difference. Surrounded by extraordinary people, inspiring leaders, and world changing projects, you will do more and become more than you ever thought possible. Our Exceptional Multi-disciplinary Team Is Unlocking The Power Of The Genome Hundreds of millions of human genomes and exomes are expected to be sequenced over the next decade, driven by steady innovations in sequencing technologies pioneered by Illumina. The enormous quantities of genomic data being generated by Illumina in collaboration with our partners worldwide represents a major opportunity to develop novel data-driven and artificial intelligence methods to extract clinically actionable information from the genome, and apply it towards improving human health. Illumina is currently seeking a highly motivated and talented Senior Experimental Scientist / Hybrid Bioinformatics Scientist who possesses both experimental and computational skills, to lead development of high throughput assays consisting of millions of single cells, and perform computational analysis of the data generated from these experiments in combination with other large scale genomics and genetics datasets. Illumina’s leading role in data generation enables us to pursue a unique genetics and genomics-first approach to discovery, with a multidisciplinary team of dedicated experimental and computational scientists working collaboratively. The Senior Experimental Scientist / Hybrid Bioinformatics Scientist will design, plan, and execute experiments in the laboratory in support of basic research and technology development around high-throughput single cell genomics assays.  This role also includes computational analysis of the data generated from these experiments.  The successful candidate is expected to demonstrate a record of innovative research and technology development as evidenced by a strong publications. Education requirements Ph.D in molecular biology, computational biology, bioengineering, or similar degree. Senior: Typically requires a minimum of 5 years of related experience with a Bachelor’s degree; or 3 years and a Master’s degree; or a PhD without experience; or equivalent work experience ( $113,300 - $169,900) Staff: Typically requires a minimum of 8 years of related experience with a Bachelor’s degree; or 6 years and a Master’s degree; or a PhD with 3 years of experience; or equivalent experience. ($ 135,400 - $203,200) Sr. Staff: Typically requires a minimum of 12 years of related experience with a Bachelor’s degree; or 9 years and a Master’s degree; or a PhD with 6 years of experience; or equivalent experience. ( $162,600 - $244,000) Required Experience and Skills On the wet lab side:  extensive expertise with experimental methods utilizing a diverse range of molecular biology techniques, including single cell assays and CRISPR, and experience with technology development for high throughput sequencing assays. On the computational side:  expertise in computational analysis in functional genomics and single cell genomics. Strong record of technical proficiency, innovation, and scientific rigor as demonstrated by publication in high-quality scientific journals. Roles and Responsibilities of the Position Design, develop and validate high throughput single cell assays consisting of millions of cells for next-generation biological discovery. Work closely with academic and clinical collaborators to integrate data and analyses from high throughput sequenci ... (truncated, view full listing at source)