Senior Bioinformatics Scientist (Algorithm Development for MRD) @ Natera
Position is available as a hybrid position in San Carlos, Bay Area, California as well as a remote position (within US). Natera is seeking a Senior Bioinformatics Scientist to join our Bioinformatics Research Team with a focus on cancer recurrence monitoring. Natera’s mission is to change the management of disease worldwide with a focus on reproductive health, cancer, and organ transplantation. The ideal candidate should have experience in sequencing algorithm development, genomics, sequencing data processing, and/or applied machine learning. This individual will analyze large and complex high-throughput cancer genomics datasets and develop novel computational methods. PRIMARY RESPONSIBILITIES: Design, implement, and validate innovative algorithms and statistical methods to analyze large-scale data sets based on insights in cancer biology and genomics Collaborate with molecular biologists and other bioinformatics scientists to answer biological questions Contribute to experimental design and quality control Foster a culture of innovation, collaboration, and scientific excellence MINIMUM QUALIFICATIONS: PhD degree in bioinformatics, computational biology, computer science, statistics, molecular biology, or a related field with a focus on cancer genomics preferred Minimum of 5 years of hands-on experience doing high-throughput genomic sequencing analysis Strong programming skills in a scientific programming language, Python strongly preferred KNOWLEDGE, SKILLS, AND ABILITIES: Track-record of developing state-of-the-art computational methods or highly cited publications Highly experienced in algorithm development, data analysis, and/or machine learning Strong domain expertise in genomics, with a preference for familiarity with cancer biology Deep understanding of sequencing data Experience with Linux command-line tools and shell scripting Ability to conduct hypothesis-driven research, visualize data, and effectively communicate results Excellent collaborative skills, self-motivation, and attention to detail Background in machine learning and statistics preferred The pay range is listed and actual compensation packages are based on a wide array of factors unique to each candidate, including but not limited to skill set, years &…
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