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 predicative 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.