Postdoctoral Fellow - Network Biologist/Computational Scientist
Sage Center for Cancer Systems Biology
Sage Bionetworks was recently awarded a four year grant from the NCI Integrative Cancer Biology Program to establish a new Center for Cancer Systems Biology (CCSB). The Sage Center focuses on interdisciplinary training in the context of the generation of probabilistic causal models of cancer for early intervention and cancer treatments.
The Sage CCSB program includes a core platform of curated datasets, mathematical models and experienced investigators mentoring complementary teams of postdoctoral fellows. Trainees will also do externships at other CCSB sites to facilitate reciprocal exchange of ideas. Models will be validated in collaboration with the Fred Hutchinson Cancer Research Center and the Netherlands Cancer Institute.
Sage is seeking postdoctoral candidates with deep expertise in physics, math or computational biology interested in interdisciplinary training in cancer systems biology. During training, candidates will be paired with trainees with complementary clinical or biological experience to forms teams that will develop predictive disease models for cancer research.
Qualifications: A Ph.D. or equivalent in physics, mathematics, statistics, computer science, electrical engineering, bioinformatics, or other relevant area is required. Experience analyzing large data sets is a plus.
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To apply for this position please contact jobs@sagebase.org
Postdoctoral Fellow, Cancer Biology
Sage Center for Cancer Systems Biology
Sage Bionetworks was recently awarded a four year grant from the NCI Integrative Cancer Biology Program to establish a new Center for Cancer Systems Biology (CCSB). The Sage Center focuses on interdisciplinary training in the context of the generation of probabilistic causal models of cancer for early intervention and cancer treatments.
The Sage CCSB program includes a core platform of curated datasets, mathematical models and experienced investigators mentoring complementary teams of postdoctoral fellows. Trainees will also do externships at other CCSB sites to facilitate reciprocal exchange of ideas. Models will be validated in collaboration with the Fred Hutchinson Cancer Research Center and the Netherlands Cancer Institute.
Sage is seeking postdoctoral candidates with significant clinical or biological experience interested in interdisciplinary training in network and computational biology. During training, candidates will be paired with trainees with complementary mathematics or network biology experience to forms teams that will develop predictive disease models for cancer research. Systems Biology
Qualifications: A Ph.D. or equivalent with strong experience and skills in cancer biology. Some understanding of computational research and experience analyzing large data sets is preferred.
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To apply for this position please contact jobs@sagebase.org
Sage is looking for exceptional candidates with strong biological backgrounds and interests in using high dimension genomic data to interpret disease processes. In particular we are seeking individuals with a background in cancer biology. The successful candidate will have a background that includes hands on laboratory research as well as the generation and interpretation of genome-wide data. Research done in this position is inherently interdisciplinary and will involve mining data across organ systems and species to develop models of biology and prospectively test the utility of those models. These models will be used to focus mechanistic experiments in many aspects of biology, including applications in therapeutic target and biomarker discovery as well as patient stratification for clinical outcome or pharmacological response. A candidate will need to demonstrate the ability to lead complex projects and to work effectively in a team environment.
Qualifications:
- PhD, MD, or equivalent in biological sciences and 3+ years of experience in an academic or corporate setting actively applying systems biology to experimental work, preferably relevant to cancer.
- Expertise in one or more of the following: microarray expression analysis, genetics of gene expression analysis, deep sequencing data analysis, statistical methods development, network methods development or complex biological data mining.
- Working knowledge of bioinformatics methods and database resources
- Familiarity with relational databases (MySQL, SQL-Server, Access, etc.)
- Basic statistical training
- Programming and computing skills using R or Matlab
To apply for this position please contact jobs@sagebase.org
Sage is looking for exceptional candidates with strong computational and analytical skills and an interest in applications relevant to the modeling of disease processes. A necessary pre-requisite for this position is hands on experience in developing network-based algorithms for representing high dimension genomic data. The candidate will work in a multi-discipline team and contribute significantly to our efforts to systematically study complex human diseases through the integration of genetics, genomics, gene expression, transcription factor binding arrays, RNAi, clinical end-points, protein-protein interaction, literature data, etc. The goal of the research is to identify causal relationships between pairs of traits, gene-gene or gene-clinical, and represent them in networks or probabilistic graphical models. Such causal networks will be used to elucidate disease or drug mechanism, to aid target discovery and target prioritization. The person in this position will be responsible to develop novel methods for integrating diverse data sources, comparing different networks (such as networks for human and mouse, or liver and adipose) and identify common features among networks or distinct pathways between normal networks and disease specific networks. A candidate will need to demonstrate the ability to lead complex projects and to work effectively in a team environment.
Qualifications:
- Ph.D. or equivalent in physics, mathematics, statistics, computer science, electrical engineering, bioinformatics, or other relevant area.
- Solid programming skills and experience with large data sets.
- 3+ years of experience in an academic or corporate setting developing systems approaches.
- Expertise in one or more of the following: microarray expression analysis, genetics of gene expression analysis, deep sequencing data analysis, statistical methods development, dynamic systems, graph theory, other network-based approaches to data analysis, or complex biological data mining.
To apply for this position please contact jobs@sagebase.org
System biology is a fast moving area. Many networks are proposed / constructed based on high throughput methods. The challenges in the field are how to compare such networks, how to extract common information and how to combine them. The answers to these important questions can guide decisions about which data to collect with limited resources and / or how to transfer knowledge from animal models to human disease.
This Post-doctoral fellow will work in a multi-discipline environment and will be responsible for developing novel methods for comparing different networks (such as networks for human and mouse, or liver and adipose) and identifying common features among networks and / or distinct pathways between normal networks and disease specific networks.
Qualifications:
A Ph.D. or equivalent in physics, mathematics, statistics, computer science, electrical engineering, bioinformatics, or other relevant area is required. Experience of analyzing large data sets is a plus.
Download Position DescriptionTo apply for this position please contact jobs@sagebase.org
System biology is a fast moving area. Network models derived from coherent sets of genome-wide data in populations provide an approach to building new models of biology that can be challenged, proofed, and refined in other populations and by experiments that perturb particular nodes or structures within molecular networks. Many of the questions that arise in this research are highly-interdisciplinary and benefit from diverse perspective, analytical approaches, and experiment designs. We seek postdoctoral fellows with strong cross-disciplinary training who are interested in leveraging the resources of the Sage Commons to develop a novel program of research.
Qualifications:
A Ph.D. or equivalent with strong experience and skills in both biology and computational research is required. Experience of analyzing large data sets is a plus.
Download Position DescriptionTo apply for this position please contact jobs@sagebase.org