BACKGROUND

RESPONSIBILITIES

• Develop, apply, document, and maintain computational tools, both for own use and t0 support analysis by biologist colleagues without formal computational training. Critically evaluate computational solutions, finding and addressing failure modes on one's own.
• Develop customized computational solutions supporting new kinds of RNA-Seq experiments, enabling the rapid, responsive use of sequencing in technology development. Understand the analytical needs of new experiments, working closely with molecular biologists. Conceive analytical/computational solutions that address the needs of such projects.
• Analyze large RNA-Seq datasets to profile and annotate transcriptomes from brain and neuronal cell populations, and provide analyses in formats accessible to a research community of biologists and geneticists.
• Follow relevant scientific literature to ensure use of optimal methods and understand emerging practices across the field.
• Contribute to reports and papers for presentation and publication and present at scientific conferences, as appropriate.
• Regularly attend and present results at Stanley Center related team meetings to share results, plan projects and experiments.
• Work with other Broad computational biologists experienced with RNA-seq, including those in the Regev and McCarroll groups, to learn, discuss, and integrate the best solution for each experiment or project.

REQUIREMENTS

• Ph.D. degree in Computer Science, Engineering, Physics, Math, Bioinformatics, Biology or other relevant scientific discipline or equivalent experience is required.
• At least tw- years post-PhD as post-doc or within a company is preferred.
• Must have demonstrated experience designing computational methods and tools, including prior experience with algorithms relevant to computational biology
• Experience with and thorough understanding of statistical analysis is required
• Familiarity with next-generation sequence data analysis tools, ideally for Illumina; in particular, experience with human or mammalian genome sequence data is preferred
• Familiarity with a range of sequence alignment tools, ideally those used for RNA-Seq (TopHat, Trinity, etc.)
• Must have demonstrated proficiency with several of the following technologies: Perl, Python, Java, Matlab, R, C, C++, Unix
• Basic understanding of molecular biology and next generation DNA sequencing
• Some familiarity with gene expression profile (microarray) data analysis
• Ability to work independently as well as part of a team in a fast-paced environment, while making necessary connections with experts in various computational analysis groups
• Self starter, highly motivated
• Excellent communication skills
• Excellent organization and time management skills

LOCALE

HOW TO APPLY