A hybrid Data & ML role at GRAIL.
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Original listing text, shown exactly as published by the company.
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Envision, design, and lead projects to evaluate and improve machine learning classifier performance for cancer detection
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Collaborate cross-functionally with scientists, engineers, and clinicians to plan, execute, and interpret experiments
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Develop high-quality, reproducible, and scalable software aligned with sound engineering principles
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Apply best practices in machine learning and statistics to generate robust, interpretable, and reliable results
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Analyze large-scale sequencing and genomics datasets to extract meaningful biological insights
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Contribute to the development and evaluation of novel machine learning methods, including deep learning approaches
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Communicate findings and present updates regularly in technical and cross-functional forums
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Contribute to scientific publications, internal tools, and production systems
These responsibilities summarize the role’s primary responsibilities and are not an exhaustive list. They may change at the company’s discretion.
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Ph.D. in Bioinformatics, Computational Biology, Computer Science, Statistics, Machine Learning, or a related field with 2+ years of relevant experience, OR
M.S. with 4+ years of relevant experience, OR
B.S. with 6+ years of relevant experience, or equivalent practical experience
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2+ years of experience applying machine learning or statistical modeling in a research or production environment
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Strong expertise in data analysis using Python or R
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Deep understanding of modern machine learning and statistical methods
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Experience developing reproducible, well-structured code in a collaborative environment
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Strong written and verbal communication skills
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Experience with modern AI techniques, including deep learning and/or large language model (LLM) training or adaptation
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Experience working with sequencing or genomics data and deriving biological insights
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Track record of scientific contributions (e.g., publications, tools, datasets, patents, or conference presentations)
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Experience with system-level programming languages (e.g., Go, Java, C, C++)
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Familiarity with version control (e.g., Git) and reproducible research practices in Linux environments
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Demonstrated ability to independently drive projects while collaborating effectively across teams…
GRAIL
Data & ML
18 open roles on Sydicom
GRAIL is a healthcare company dedicated to the early detection of cancer. They develop innovative liquid biopsy technology, including the Galleri test, to identify multiple cancer types from a single blood sample.
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