Karius is building the next generation of infectious disease diagnostic assays. We recently launched the first clinical diagnostic test that uses a minimally invasive blood draw to detect >1,000 pathogens regardless of the source of infection. The test relies on the detection of small amounts of cell-free nucleic acids released into plasma.
We are seeking a candidate to work in a rapid, iterative research environment at the interface of our analytics, molecular biology, and medical teams. You will use rigorous quantitative reasoning to analyze and design experiments that allow us to understand more deeply, troubleshoot, and improve our existing and future assays. You will combine clinical and genomic data to gain novel insight into the interaction between pathogens and disease. This role sits at the heart of where important decisions are made about our technology, and a creative and energetic candidate will have the opportunity to shape the future of our assays and infectious disease medicine!
· Generate hypotheses, design experiments, and glean insights that improve the understanding of the genomic signatures of pathogen infection
·Design and implement algorithms and statistical and machine learning models to drive discovery and interpretation using genomic, metagenomic, and other kinds of biological and clinical data
·Produce robust, reproducible research findings out of multiple sources of heterogeneous data
·Collaborate with the scientists, physicians, and engineers to make meaningful contributions to scientific discoveries and the invention of technologies
· PhD in computational biology, statistics, or related fields
· 0-2 years of post-graduate experience
· Demonstrated expertise in analysis and visualization of biological data to drive insight and decision-making
· Experience with and understanding of modern statistics and/or machine learning
· Familiarity and experience with bioinformatics tools, approaches and workflows, particularly those related to next-generation sequencing data analysis
· Familiarity with a range of relevant laboratory techniques (either through hands-on work or from collaborations with laboratory-focused colleagues)
· Proficiency in working with large-scale datasets in Python or R
· Creativity in generating hypotheses and proposing experiments and analyses to test them
· Excellence at communication and collaboration within a cross-functional team