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Lilly Genetic Medicine is looking for a talented and motivated computational scientist to join our team in Cambridge, MA. We pursue cutting-edge research in a highly interdisciplinary environment to enable the next generation of RNA therapeutics. We work in close collaboration with colleagues in drug delivery and across therapeutic areas.
The successful candidate will have a strong research track record working with computational methods in combination with experiment. The candidate will collaborate within a multidisciplinary team to perform deep data analyses and build core informatics capabilities in support of research decision making to drive discovery research forward to next generation of RNA therapies.
Key Responsibilities:
Apply state-of-the-art computational and informatics approaches to support data-driven computer-aided design that helps drive all aspects of discovery programs forward
Develop or bring-in tools to build computational infrastructure to implement best methods for analysis, visualization and interpretation of complex experimental readouts
Facilitate interaction between experimental and computational scientists using data-driven methodologies focused on expanding our understanding of RNA therapeutics within a highly multi-disciplinary team of computational scientists, software engineers, architects, biomaterials engineers, chemists, and biologists
Establish best practices for analysis and interpretation of high-dimensional formulation, in vitro and in vivo data that empowers efficient hypothesis-driven design of novel biomaterials
Educate and support the scientific community in best practices for complex data analysis, visualization and interpretation
Identify emerging opportunities and new strategies for computational and informatics methodology development and improvement
Coordinate and lead research collaborations with both internal and external partners
Basic Requirements:
Ph.D. in area with multidisciplinary focus in computational science, e.g., Computational Biology, Bioengineering, Applied Mathematics, Bioinformatics, Cheminformatics, or related field.
Additional Skills/Preferences:
A demonstrated knowledge of working in fast-paced exploratory research programs
Deep domain experience with state-of-the-art computational tools, especially for methods in data science and informatics
Creative problem solving ability with demonstrated capacity to draw conclusions from complex datasets and present them in clear and understandable ways
Strong written and oral communication skills
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