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BioInformatics
Scientist
Job
Code: 10-TR25
Location:
Cambridge, MA
Description
We
are seeking a highly motivated, independent bioinformatics scientist to join a
group of scientists, analysts and programmers to develop tools and
methodologies for large-scale gene expression data analysis. The group
supports a variety of research projects in target and drug discovery as well as
biomarker development for AVEO’s growing pipeline of novel anti-cancer drugs,
AVEO’s
Translational Research program utilizes a novel platform combining proprietary,
inducible tumor models and bioinformatics approaches to discover, validate and
generate therapeutics against molecular targets in oncology. We have
generated large populations of tumors that exhibit inter-tumor heterogeneity
similar to that seen in human tumor populations. Each tumor has been
characterized by microarray, array CGH, histology, key signaling pathways as
well as sensitivity to a variety of cancer therapeutics, including AVEO’s
clinical stage drug candidates. This well-characterized tumor population
model system enables the correlation of gene expression and DNA copy number
with drug efficacy, providing an attractive platform for the creative
innovative bioinformatics scientist to develop and test translational
hypotheses. Our goal is to use the platform to inform clinical trial
design regarding tumor, tumor subtype and patient selection for AVEO’s own
clinical stage oncology drug candidates.
Responsibilities
The
candidate will:
- Participate
in generating, processing and evaluating large oncology-related
datasets.
- Work
on a variety of high-dimensional data projects largely centered on
biomarker discovery and develop biomarkers for response to therapy and
disease subtype classification
- Execute
a wide range of computational and analytical tasks, including developing
and implementing algorithms for target identification and biomarker
discovery.
- Integrate
publicly or commercially available genomic data with novel experimental
data.
- Identify and execute innovations
(computational, statistical, and strategic) that will quantifiably improve
Projects
- Identify
new datasets and data mining techniques relevant to cancer target and drug
discovery
- Develop
and test novel methods and algorithms, working with academic collaborators
where opportunities arise
Qualifications
& Requirements
·
PhD
in Biology, Bioinformatics, or equivalent, as well as 2+ years of full time
experience in an academic or biotechnology industry lab, or equivalent
experience.
·
Interest
in, and working knowledge of cancer biology,
·
A
solid understanding of statistics. Have experience with a broad range of
statistical methods for classification and prediction, e.g., linear models,
machine learning, and other multivariate analysis methods.
·
Programming
experience and ability to write R and Perl script.
·
The
candidate will have experience with large-scale genomics data and a solid
understanding of bioinformatics data bases (eg: GenBank, RefSeq, dbSNP etc)
·
Experience
with some bioinformatics software such as: Spotfire, Partek, Ingenuity, GeneGo,
Balst, and Blat.
·
The
candidate will have the ability and interest in learning new techniques and
skills in accordance with evolving research program needs.
·
Candidates
with a proven ability to work efficiently in a team setting, and excellent
communication skills are preferred.
About
AVEO
AVEO
Pharmaceuticals (NASDAQ: AVEO) integrates a proprietary cancer biology platform
with drug development and commercial expertise in its efforts to discover and
develop targeted cancer therapeutics. The company's lead product, Tivozanib, is
an oral, triple VEGF receptor inhibitor with potential for a best-in-class
profile. Tivozanib is currently being investigated in a global, randomized
Phase 3 clinical trial called TIVO-1 comparing Tivozanib to Sorafenib in
advanced kidney cancer, as well as additional clinical studies in other solid
tumor types. AVEO's proprietary, integrated cancer biology platform offers the
company a unique advantage in oncology drug development that both increases the
probability of clinical success and provides a discovery engine for high-value targets.
This approach has resulted in a promising pipeline of monoclonal antibodies
against novel targets including HGF, ErbB3, RON, Notch and FGFR. For more information, please visit
the company's website at www.aveopharma.com.
Please
forward resumes to hr@aveopharma.com.