Postdoctoral Fellow in Computational Biology
Sage Bionetworks Center for Cancer Systems Biology - Seattle, WA
Postdoctoral Fellow in Computational Biology,

Sage Bionetworks Center for Cancer Systems Biology, Seattle, Washington

As a Center within the National Cancer Institute’s Integrative Cancer Biology Program

(ICBP), we are recruiting qualified candidates for a fully-funded two year postdoctoral training

program.

At Sage Bionetworks, our focus is on innovation and execution. Accordingly, we seek

driven fellows who want to engage in innovative systems biology research while executing their

ideas, using tools and best practices to ensure their findings have the best opportunity for

crossing the breach between discovery science and bedside application.

Sage Bionetworks is a nonprofit biomedical research organization located at the Fred

Hutchinson Cancer Research Center in Seattle, Washington. It includes experts in systems

biology, statistical genetics, network models, machine learning, and software engineering, all

applying the principles of open-access science to the common goal of developing predictive

models of disease.

We provide a dynamic training environment in which fellows will engage in multi-

disciplinary research by working with Sage Bionetworks senior scientists, software engineers,

and a large network of experimental collaborators at the Fred Hutchinson Cancer Center and

other institutions. An important component of this fellowship will include engaging our software

development team to perform data intensive analysis by leveraging cloud-based computing to

benchmark and iterate models of disease that allow them to easily plug in to an architecture

available to the entire scientific community.

The hub for this training incubator is Synapse, a cloud-based open-access platform for

developing, testing, validating and deploying systems biology models of disease at the same

time as serving as a resource for curated and quality-controlled datasets and models.

Training at Sage Bionetworks provides an opportunity to explore advanced modeling

approaches in cancer while learning techniques in software development, cloud and distributed

computing.

For each project a Fellow is engaged in the goal will be to publish it in two settings: as an

innovative scientific approach to a problem in cancer biology, and as a method that is also

deployed as an accessible service in Synapse.

Fellows will complete the program with a unique skill set that enables them to enter

academia, where their under-standing of how reproducible and robust computation informs

experimentation, and vice-versa is critical in “big data” science; and industry, where their

experience with the challenges of connecting biologically-driven hypotheses with well-

engineered computational workflows are crucial in diagnostic and pharmaceutical

development.

Qualifications

PhD in computational biology, biostatistics, bioinformatics, computer science, applied

mathematics, physics or other heavily quantitative area is required.

The ideal candidate will have advanced training in an analytical discipline such as Bayesian

statistics, graphical models, or optimization.

Strong experience in cancer biology research or analyzing biological pathways preferred.

An MD or experience analyzing clinical data is a plus.

Experience in software engineering, cloud computing, or large-scale scientific computation

is a plus.

To apply, send your CV and cover letter to postdoc.post@sagebase.org

www.sagebase.org

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