[Bioc-devel] Bioconductor Employment: Statistical Research Associate

Martin Morgan mtmorgan at fhcrc.org
Thu Dec 1 01:25:11 CET 2011

Bioconductors! -- please see the job description below for a Statistical 
Research Associate opening with the Bioconductor group. See


choose 'Search Jobs' at the Fred Hutchinson Cancer Research Center, and 
look for job ID 24198 for a complete job description. Please contact me 
directly with any questions.




The Bioconductor project (http://bioconductor.org) seeks a creative and 
motivated individual to join our bioinformatics team. Bioconductor 
develops and distributes open-source, open-development software for 
analysis and comprehension of high-throughput genomic data from 
sequencing and other sources. Bioconductor is based on the R language 
for statistical analysis, with more than 500 software packages developed 
internally and by our vibrant user community.


This unique opportunity links scientific research with software 
development. The applicant will work under immediate technical direction 
to analyze and comprehend high-throughput sequence data, translating 
their research insights into appropriate Bioconductor work flows.


This position involves bioinformatic analysis of high-throughput 
sequence data  using R / Bioconductor tools. The applicant will, in 
consultation with other team members, identify appropriate analytic 
approaches and work flows. The applicant will implement the analysis, 
and arrive at scientifically sound conclusions. The applicant will 
identify common work flows, communicating these to other team members. 
Secondary duties involve participation in ongoing Bioconductor tasks, 
including maintenance of contributed packages, technical previews of new 
contributed packages, and tasks related to twice-yearly releases. There 
are opportunities for  user support through our mailing list, regular 
course offerings, and an annual conference.


1) Master’s degree or comparable experience in biological science, 
bioinformatics, or related disciplines.

2) Familiarity with programming languages, for example C, Matlab, and 
especially R.

3) Familiarity with statistical concepts and methods.

Recommended qualifications include:

1) A strong biological background.

2) Experience with managing high-volume genetic data, such as from 
next-generation sequence pipelines, and with relevant public annotation 

3) Familiarity with bioinformatic work flows, especially analysis of 
sequence data from RNA, ChIP, and DNAseq experiments.

4) Experience with software development best practices appropriate for 
small teams, for instance use of version control, unit tests, agile 
project management, and creation of end-user documentation.
Computational Biology
Fred Hutchinson Cancer Research Center
1100 Fairview Ave. N. PO Box 19024 Seattle, WA 98109

Location: M1-B861
Telephone: 206 667-2793

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