Postdoctoral Fellow, Computational Oncology
Sage Bionetworks is currently recruiting for a computational biology postdoctoral fellow with an interest and background in cancer research. This position presents the opportunity to focus on a diverse set of questions in cancer. Ideal candidates will have a background in pre-clinical and translational medicine, and an appreciation of efforts to incorporate `omics’ data into clinical practice.
Specific Responsibilities Include
- Design and develop research projects from inception to publication in various cancer domains including:
- Prognostic modeling of patient outcomes
- Predictive modeling of drug response
- Analysis of functional screen data e.g. drug response, siRNA
- Integrative genomic modeling
- Design and develop algorithms for interrogating and interpreting complex genomic data.
- Interact with large cancer systems biology research consortia to ask novel questions spanning the data collected by each individual research group.
- Work closely with Sage and DREAM scientists to develop DREAM Challenges around impactful questions in cancer research.
- Candidate will hold a Ph.D. in computer science, bioinformatics, or related quantitative discipline.
- Experience working with high dimensional genomic data, such as sequencing data, gene expression, genotype, CNV, sequence and/or data from other high throughput biological technologies.
- Demonstrated excellence in research with evidence of advancing an area of computational biology.
- An understanding of advanced machine learning or statistical techniques, such as probabilistic graphical models, Bayesian inference, and optimization methods.
- Software development experience, including strong programming skills in a high level language such as Python, R, or Java.
- A passion for open-access innovation.
- Strong collaboration, teamwork, and communication skills.
- A desire to change the world and contribute to the elimination of human disease.
About Sage Bionetworks
Sage Bionetworks, is a non-profit organization located in Seattle and dedicated to advancing biomedical research through the implementation of reproducible, open science. Using cutting edge machine-learning methodologies, in collaboration with scientists around the world, we build predictive models of disease-related phenotypes through integrative analysis of large-scale genomic and imaging data sets. Sage offers a comprehensive benefits package, including relocation benefits to bring the right talent to the team.
To apply for this position, please send your CV and cover letter to: firstname.lastname@example.org