We are seeking an innovative, collaborative and accomplished Scientist to lead our computational sciences team to support the development of RNA medicines using our next-generation, state-of-the-art technology.
Responsibilities:
Establish, manage and motivate a team of computational scientists to support all computational biology applications necessary to develop and execute a compelling portfolio of RNA targets.
Create and implement a suite of computational biology tools, programs and hardware to support all RNA research activities, which may include:
Use genome-scale data to conduct disease mapping and other statistical analyses to generate target hypotheses. Collaborate with research teams to prioritize and validate drug discovery targets.
Use and enhance existing bioinformatics tools to analyze NGS data and to establish algorithms for the optimal, automated selection of RNA constructs.
Communicate scientifically rigorous findings via verbal and written communications, visualizations, and presentations.
Apply or develop new tools or data-mining techniques for integrative analysis and visualization of large datasets.
Qualifications:
A Ph.D. in bioinformatics, computer science, biology, genetics, or equivalent field.
10 years of experience in computational biology and genomics required.
Supervisory and leadership experience.
Experience with molecular research techniques (qPCR, ddPCR, NGS library prep) is ideal.
Proficiency in evaluating large-scale genomic datasets.
Robust knowledge of one or more programming language (eg. Python, C++, R, etc) and of protein modeling software (ideally Rosetta).
Strong scientific background and publication record with proven high levels of performance.
Experience with machine learning algorithms and data mining methods.
Familiarity with pathway analysis.
Experience with cloud computing is a plus.
Ability to work independently while also building relationships with colleagues.
Ability to adapt to increasing scope and complexity of work brought on by growth/change and helps others manage through change.
