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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.
Position Summary
To accelerate the adoption of clinical sequencing, Illumina is recruiting a world-class Machine Learning Scientist and Software Engineer to work on the development of novel deep learning algorithms and production-ready software for deciphering the effects of genetic variants in the human genome.
Major aims would include modeling the effects of genetic variants on gene function, transcriptional regulation, and diagnosis of pathogenic variants in patients with cancer or rare genetic diseases. A key objective is to develop robust, scalable software implementations of research results and publish these findings in peer-reviewed journals. This will improve the accuracy, throughput, and reproducibility of genome interpretation, thereby removing barriers to the clinical adoption of whole genome sequencing. In addition to strong analytical and software development skills, this position will require a high degree of initiative, autonomy, and scientific collaboration.
Responsibilities
- Contribute to the development of deep learning algorithms for interpreting human genetic data, supporting efforts to identify pathogenic genetic variants using information from clinical phenotypes, protein structures, and genomic data.
- Implement, test, and document software modules under the guidance of senior team members, with a focus on reliability, scalability, and efficiency.
- Support collaborations with internal and external partners by preparing datasets, running analyses, and contributing to project deliverables.
- Assist in preparing research results for internal reports, presentations, and publications, and contribute to integrating methods into software products for the genetics community.
Preferred Requirements
- Knowledge in deep learning, statistics, bioinformatics, and/or genomics.
- Knowledge in Full stack software development and deployment of scientific software.
- Familiarity with software development best practices, including version control (e.g., Git), testing frameworks, and continuous integration/continuous deployment (CI/CD).
- Possesses strong communication skills
- Be willing to work in a fast-paced, competitive environment, and hold a strong record of successful delivery of complex scientific projects and publications under tight timelines.
- BS or MS in computer science, bioinformatics, computational biology, or a related field.
Key Skills
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