Entering edit mode
Bioconductors! -- please see the job description below for a
Statistical
Research Associate opening with the Bioconductor group. See
http://fhcrc.org/about/jobs/index.html
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.
Best,
Martin
----
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.
SCOPE OF RESPONSIBILITIES:
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.
MAJOR DUTIES:
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.
MINIMUM QUALIFICATIONS:
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
resources.
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