Bioinformatics Scientist The New York Stem Cell Foundation (NYSCF) is a rapidly growing and highly successful nonprofit whose mission is to accelerate cures through stem cell research. NYSCF is seeking a Bioinformatics Scientist to support the ongoing efforts of both The NYSCF Global Stem Cell Array as well as the wider research laboratory. This position reports to VP, Automation Systems and Stem Cell Biology, working closely alongside software engineers, research scientists, and operations. The Bioinformatics Scientist will be responsible for the organization, storage, and analysis of biological and biochemical data as it pertains to research performed at NYSCF. The position also requires learning essential experimental methods and laboratory science to support cutting-edge stem cell research and communicate with laboratory scientists about points of issue and excitement within their data. Responsibilities: Design and develop computational tools and pipelines for various bioinformatics tasks including genomic alignment, assembly, variant detection, and expression analysis with data generated across a variety of platforms. The organization, storage, and development of tools to provide optimal access to both raw and processed data. Development of novel algorithms/models for enabling predictions based on collected data. Minimum Qualifications Proficiency in Python and/or R, SQL, and UNIX/Linux as well as experience with Bioconductor or related tools. Experience with pandas, numpy, and scipy for the efficient parsing, handling, and analysis of numerical and text-based data in Python. Familiarity with matplotlib and associated libraries in Python, as well as ggplot2 and associated libraries in R, for generating complex graphics based on large data sets. A solid foundation in hypothesis testing, statistical inference, and predictive modeling is required. Experience with Amazon Web Services’ RDS, EC2, and S3 cloud computing and web services. Willingness to learn advanced statistical and algorithmic techniques, such as relevant machine learning models and design of experiment (DoE). MS in Bioinformatics preferred. #J-18808-Ljbffr nyscf
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