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 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.
Listed responsibilities are an essential but not exhaustive list of the usual duties associated with the position. Changes to individual responsibilities may occur due to business needs.
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.
Preferred Experience/Education
BS or MS in computer science bioinformatics computational biology or a related field.
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