Careers @ Sage Bionetworks

Sage Bionetworks is expanding its interdisciplinary team to accelerate the development of network models of biology across a variety of disease areas and species.

If you thrive in dynamic and intense start-up environments and enjoy the challenges of designing and implementing new approaches to computational biology, genomics and therapeutic discovery, we invite you to explore the career opportunities at Sage Bionetworks.

Sage Bionetworks seeks talented professionals committed to excellence and innovation who can balance interdisciplinary teamwork and individual initiative in a mission-based research environment.

Sage Bionetworks offers competitive salary packages in an outstanding urban research setting. Benefits include health and disability insurance, a 403(b) retirement plan, relocation, transportation subsidies, and a flexible spending plan.


Senior Software Engineer – Scientific Programming

We currently have an opening for a Software Engineer to join the team responsible for the design, creation, testing, and deployment of the Synapse software infrastructure. The Synapse system will provide scalable access to clinical genomics data and compute resources to scientists at Sage and around the world. This is an opportunity to work on a software platform with significant impact on human health research, and to work in a fast-paced entrepreneurial environment. The position will focus on the development of Synapse’s client-side integrations with data analysis tools like R and Python. Ability to work on cross-functional teams supporting scientific end users in the use of Sage informatics tools is expected.

Requirements

  • BS or MS in Computer Science or equivalent
  • Experience building, shipping, and supporting commercial or academic software products with significant user bases. Proven experience developing new products in rapidly changing engineering environment strongly preferred.
  • Versatile and strong programming skills with the ability to work with a variety of programming languages, with a focus on R, Python, and Java
  • Strong understanding object oriented design and programming, and design patterns
  • Experience developing software tools used by scientific user communities. Background in data analysis, machine learning, and statistics is highly beneficial. However, the position is a software-engineering focused position designed to develop tools and support a scientific user base, not a scientific research position.
  • Experience with one or more of the following:
    1. Bioinformatics / genomics data and use cases
    2. Machine learning / statistics / data analysis
  • Ability to rapidly assess and integrate new software technologies into a complete solution
  • Experience with
    1. Unix/Linux
    2. N-tier enterprise software architectures
    3. Relational database systems and SQL
    4. Web Services
  • Practical agile development lifecycle experience. Familiarity with software development tools (Eclipse, Jira Studio, Maven, Git etc.)
  • Strong verbal, written, and organizational skills
  • Ability to thrive in a dynamic start-up environment, and collaborate on evolving research projects
  • Self-starter with the ability to multitask
  • Experience with one or more of the following desirable:
    1. Cloud Computing Infrastructures especially AWS, SaaS architectures
    2. Open source software development

Sage Bionetworks offers a salary for the position, rate dependent on experience, and competitive benefits package. To apply, please forward your CV and cover letter to: sw.jobs@sagebase.org

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Computational Biology Positions

Sage Bionetworks is a world-leading nonprofit biomedical research organization dedicated to: (1) developing predictive models of disease-related phenotypes through integrative analysis of large-scale genomic data sets; (2) building and supporting an open source compute platform and database to more effectively harness genome-scale data by enabling disease models to be evolved by contributor scientists with a shared vision to accelerate the elimination of human disease.

We are seeking exceptional candidates with strong computational and analytical skills, as well as a desire to work in a multi-disciplinary team. Candidates will work with our large network of experimental and computational collaborators at the Fred Hutchinson Cancer Research Center, Columbia, UCSD, Stanford, Mt. Sinai, Harvard, companies such as Roche, Takeda, AstraZeneca, and with our team of professional software engineers and computational biologists to implement cloud-based computational methods to analyze terabyte-scale genomic datasets.

Applicants are expected to have achieved recognition appropriate for their level as an expert in an area of data-intensive computational systems biology and be able to develop independent lines of research. We welcome applications for:

    • Scientific Programmer, Computational Biology
    • Research Fellow, Computational Biology

Responsibilities:

  • Develop and implement predictive models of disease phenotypes through integrative analysis of high-dimensional genomic data.
  • Develop statistical and machine learning approaches to combine information from diverse data types and prior knowledge derived from related experiments and biological databases.
  • Assist in experimental design to validate computational predictions.
  • Foster and maintain collaborations with experimental researchers.
  • Work with software development team to implement scalable cloud-enabled workflows to disseminate analytical advances to the research community.
  • Publish computational innovations and research discoveries in leading journals.
  • Develop grant proposals for original research projects.

Required Qualifications for All Positions:

  • An understanding of advanced machine learning or statistical techniques, such as probabilistic graphical models, Bayesian inference, and optimization methods.
  • Strong communication skills.
  • Strong publication record.
  • A desire to change the world and contribute to the elimination of human disease.

Required Qualifications for Senior Scientists:

  • Ph.D. degree in computer science, math, bioinformatics, or relevant quantitative scientific discipline.
  • Demonstrated excellence in research with evidence of advancing an area of computational biology.
  • 5 years of relevant work experience analyzing high-throughput genomics data.

Required Qualifications for Research Fellows:

  • Ph.D. degree in computer science, math, bioinformatics, or relevant quantitative scientific discipline.
  • 2 years of relevant work experience analyzing high-throughput genomics data.

Required Qualifications for Scientific Programmers:

  • Bachelors or Masters degree in computer science, math, bioinformatics, or relevant quantitative scientific discipline.
  • 5 years of industry or academic experience analyzing high-throughput genomics data.

Desirable Qualifications:

  • Advanced programming skills.
  • Experience in a professional, team-oriented software development environment.
  • Experience analyzing high-dimensional genomic data, including DNA or RNA sequencing, gene expression, epigenetics, and SNP array data.
  • Demonstrated leadership roles and organizational skills.
  • A passion for open-access innovation.

For more information on Sage Bionetworks and our Seattle-based team of researchers, visit www.sagebase.org. To apply, please send your CV and a cover letter to: compbiojobs@sagebase.org.

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Software Engineering Intern

Position Summary

Do you want to change how scientists approach basic and clinical life science research and how pharmaceutical companies develop cures for disease? Sage Bionetworks is a medical research organization dedicated to building advanced predictive models of human disease.  Our primary objectives are two-fold: to build and support an open access platform and databases for building innovative disease models; and to interconnect scientists as contributors to evolving, integrated networks of biological data.  See our recent feature in the Seattle Times for more information.

We currently have an opening for a Software Engineering Intern on the team responsible for the design, creation, testing, and deployment of the Synapse software infrastructure. The Synapse system will provide scalable access to clinical genomics data and compute resources to scientists around the world. This is an opportunity to work on a software platform with significant impact on human health research, and to work in a fast-paced entrepreneurial environment.  As part of the Sage technology team you will:

  • Own a software development project adding new features to the Synapse system in areas such as cloud computing, scientific / statistical analysis, data visualization, or social networking
  • Collaborate with a senior engineer mentor in a collaborative environment including team software design and technology review meetings
  • Develop experience writing code for and working on a cloud computing platform
  • Learn practical professional engineering skills working on a team that utilizes agile development methods
  • Work on a small team (~7 people) and gain exposure to the complete software development lifecycle; we deploy new code for our scientist users several times a month
  • Write open-source code; your resume can link to your code written during your internship!

Requirements:

  • Enrollment in an accredited degree program working towards a degree in computer science or a related discipline with at least one term to finish after the completion of the internship
  • Ability to commit to a 6 month, full time position
  • Experience with:
    • Variety of operating systems including Unix/Linux/Windows
    • A variety of programming languages (Java, Python. etc.)
    • Web design languages (Javascript, Html, CSS)
    • Databases (MySQL, etc.)
  • Some familiarity with software development tools (Eclipse, Maven, Jira Studio, etc.)
  • Strong verbal, written, and organizational skills
  • Self-starter with the ability to multitask and drive projects to completion

Sage Bionetworks offers an hourly salary for this position, rate dependent on experience. To apply, please forward your CV and cover letter to: sw.jobs@sagebase.org.

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Cancer Systems, Senior Scientist

We seek exceptional candidates with strong domain experience at the intersection of high-dimensional genomic data and (1) basic cancer biology, (2) clinical cancer biology. Such candidates will have exceptional analytical skills, a strong interest in developing predictive cancer phenotypic models (predictive and/or prognostic biomarkers) and the ability and desire to work in a multi-disciplinary team of biologists, statisticians, machine learning experts, and software engineers.

There will be opportunities to collaborate with our large network of experimental and computational partners at the Fred Hutchinson Cancer Research Center, Columbia, UCSD, Stanford, Mt. Sinai, Harvard, companies such as Roche, Takeda, Astra Zeneca, and with our team of professional software engineers and computational biologists to implement cloud-based computational methods to analyze terabyte-scale genomic datasets.

As a senior scientist, the candidate is expected to lead original research projects advancing new directions in cancer genomics.

Sage Bionetworks is a world leading computational biology research organization dedicated to: (1) open science; (2) developing predictive models of cancer-related phenotypes through integrative analysis of large-scale genomic data sets; (3) building and supporting an open source compute platform and database to more effectively harness genome-scale data by enabling cancer phenotypic models to be evolved by contributor scientists with a shared vision to accelerate the elimination of human disease.

Responsibilities

  • Develop and implement predictive models of disease phenotypes through integrative analysis of high-dimensional genomic data.
  • Develop strategies to extend experimental cancer models to clinical application
  • Foster and maintain collaborations with experimental researchers.
  • Work with software development team to implement scalable cloud-enabled workflows to disseminate analytical advances to the research community.
  • Publish computational innovations and research discoveries in leading journals.
  • Design and lead a multi-investigator research project with industry or academic collaborators.
  • Provide expertise and mentorship to Sage Bionetwork researchers.

Required Qualifications

  • Ph.D. degree in cancer biology, molecular biology, genetics, or genomics.
  • Or M.D. degree with oncology-relevant training.
  • Demonstrated excellence in research with evidence of advancing an area of cancer genomics.
  • Strong communication skills.
  • Strong publication record.
  • 5 years of relevant work experience analyzing high-throughput genomics data.
  • An understanding of advanced machine learning or statistical techniques, such as probabilistic graphical models, Bayesian inference, and optimization methods.
  • A desire to change the world and contribute to the elimination of human disease.

Desirable Qualifications

  • Experience in biomarker generation or validation
  • Experience in early phase clinical trials or therapeutic development
  • Advanced programming skills
  • Experience in a professional, team-oriented software development environment.
  • Experience analyzing high-dimensional genomic data, including DNA or RNA sequencing, gene expression, epigenetics, and SNP array data
  • Demonstrated leadership roles and organizational skills
  • A passion for open-access innovation

For more information on Sage Bionetworks and our Seattle based team of researchers, visit www.sagebase.org. To apply, please contact: cancerbiojobs@sagebase.org.

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Postdoctoral Fellowship Opportunities


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

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 understanding 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.jobs@sagebase.org

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