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
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
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
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 firstname.lastname@example.org
Turing-Jobs - 14 months ago