The Broad Institute of MIT and Harvard is seeking a highly motivated individual to perform analysis of new datasets generated by RNA, ChiP and RIP sequencing experiments that support the overall research objective of an integrative computational and experimental lab in a fast-paced and dynamic environment. This research group recently identified a new class of mammalian genes termed lincRNAs that exert their regulatory influences on the genome in unknown ways. Our goal is to identify lincRNA-protein, lincRNA-DNA, and lincRNA-RNA interactions. Collectively, this research experience will allow a candidate to work both independently and amongst a highly collaborative team participating in the challenging and incredibly exciting field of lincRNA biology.
The Broad Institute provides a vibrant research environment with close links to top academic institutions across the Boston Area and provides the potential for your contributions to be used and recognized worldwide.
The successful candidate will interact with members of various Broad platforms to ensure proper experimental design, analysis and technical concerns are met. This person will help develop and implement algorithms to analyze new data and integrate it with other data sets already available. The candidate will also help with the generation of tools needed for manipulating and preparing data for display; transferring data to external collaborators and data repositories; and will also help maintain, support, and document shared tools, code base, and data sets.
KEY RESPONSIBILITIES / ESSENTIAL FUNCTIONS
• Use existing computational pipelines to analyze new data sets essential to the overall project success.
• Design and assists in developing statistical methods and computational algorithms for analyzing large-scale datasets.
• Analyze results and identify methodological problems. Adjust algorithms as needed to ensure project completion in a timely fashion.
• Gather, summarize and report all experimental results to manager.
• Consults with other senior scientists or scientific literature as needed.
• Assist with preparation and presentation of data.
Bachelor’s degree in bioinformatics, mathematical, physical, or other computer science related field.
Masters degree in bioinformatics, mathematical, physical, or other computer science related field.
Significant experience in computer programming and computational biological applications. A strong background in statistics and biology.
Excellent skills in at least one programming language required, preferably Python or Java. Additional experience or potential in R and MATLAB are also preferred.
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