Nuanced Health is a seed-stage, venture capital-backed biotechnology company that is reimagining the drug development process in order to discover, develop, and evolve therapeutics. We believe that a better understanding of the biological heterogeneity among us can inspire novel therapeutics and maximize the efficacy of existing ones. At Nuanced Health, we combine in vivo techniques with computational methods to envision a drug development process that addresses our unique biology and builds treatments that work for everyone. We are a multidisciplinary company, motivated to build a mutualistic environment where engineers and scientists work synergistically to create a revolutionary product on a category-defining platform for the life sciences industry.
Nuanced Health is founded on enabling and integrating teams and systems to have a greater impact – a core principle that we apply toward our people and our product.
The ability to analyze and interrogate the diverse molecules in metabolomic and lipidomic data directly enables the success of Nuanced Health’s mission to change drug discovery. A critical aspect of that is the ability to incorporate analyses from mass-spectrometry based datasets with those from other high-throughput data in order to compile multi-omic results.
As part of the computational team, you will deliver research that directly impacts and supports the growth of the organization through the design, execution, and analysis of experiments. You should be excited about analytical solutions that provide actionable insights from biological data. These results will be derived from robust, scalable, and reproducible cloud-based computational workflows that rely on fundamental biological concepts and integrate novel methods and concepts in bioinformatics or machine learning where appropriate.
As a Computational Biologist, Metabolomics, you will be primarily responsible for driving scientific progress as it relates to the mass spectrometry program as part of the larger platform. You would be joining a team of microbiologists, immunologists, researchers and computational scientists and engineers, so an ideal teammate is intentionally curious, highly adaptable, committed to learning, and passionate about innovation, all within a dynamic startup environment.