mHealth (Digital Health) Analytics Intern/Co-Op

mHealth (Digital Health) Analytics Intern/Co-Op

Sage Bionetworks is currently looking to fill an internship position in our mobile health analytics group. We are actively running large scale mobile based clinical studies that use wearable sensors and smartphones to quantify symptoms of disease and health. If you are looking to build a career in health informatics and want to be part of the mobile health revolution, we would love to hear from you!

Position Overview
The intern will be mentored by staff scientists at Sage Bionetworks, with opportunities to contribute to active mobile health studies. Benefits of interning at Sage include opportunities to work on unique mobile health datasets and scientific projects, learn professional data science and software engineering skills in the context of mobile health, while working on open source projects and engaging in open science. You will analyze real time data streaming from thousands of participant phones and help us design the next generation of research and health applications.

Specific Responsibilities Include:

  • Process and integrate remote sensor data using cloud computing.
  • Prototype and test new services for mHealth data including visualization, documentation, and computation.
  • Perform signal processing and feature extraction from sensor data.
  • Apply supervised and unsupervised machine learning methods to quantify disease.
  • Automate the execution of new analysis methods using scripting and statistical programming

Basic Qualifications:

  • Ability to commit to a minimum of 6-months with a possibility of extension and/or conversion to a full-time position.
  • Enrollment in an accredited degree program working towards a degree in bioinformatics, statistics, electrical engineering or a closely-related discipline.
  • Fluent programming skills in R, Python or Matlab.
  • Experience with computing in a Unix/Linux environment.

Additional Skills/Preferences:

  • Graduate students are strongly preferred; exceptional junior- or senior-level undergraduates may be considered.
  • Strong verbal, written, and organizational skills.
  • Prior demonstrable experience through coursework or projects in data science, algorithms, remote sensing, signal processing and statistics
  • Experience with analyzing time series data in measuring biological processes such as accelerometers, force plates, and heart rate monitors is a plus.

About Sage Bionetworks
Sage Bionetworks is a Seattle, WA based non-profit organization dedicated to advancing biomedical research through the implementation of open and reproducible 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. To enhance collaborative efforts, we provide a collaborative compute platform ( for sharing research insights in a transparent, reproducible fashion.

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Current Positions

Computational Oncology

The Computational Biology group focuses on developing integrative probabilistic models for prediction of disease phenotypes and validating of hypotheses generated by novel methodologies. Currently opportunities include: positions in Oncology focused on conducting original research in analyzing large-scale high dimensional genomics data to develop predictive models of cancer phenotypes. Positions in collaboration with the recently merged Sage/DREAM effort, focused on designing and implementing crowd-sourced collaborative challenges around cancer phenotype prediction problems. Positions in stem cell bioinformatics with a focus on development of the data and analysis bioinformatics portal for the Progenitor Cell Biology Consortium, as well as research projects on modeling molecular mechanisms underlying stem cell differentiation.

Digital Health

Sage Bionetworks’ digital health program is designed to improve disease characterization through the use of sensor-based technologies and bi-directional feedback to improve health monitoring and provide quantitative metrics to assess disease impact on health and on quality of life. We maximize the insights gained from these efforts by providing them through Synapse, a collaborative compute platform. Our mHealth team includes expertise in software engineering (both iOS and Android), clinical study design and development, data governance and data analysis. We are actively involved in projects across a range of disease areas and within the Precision Medicine Initiative.

Neurodegenerative Research

An overarching goal of the Neurodegenerative Research (NDR) group is to improve understanding of the molecular mechanisms of neurodegeneration via computational analyses of high-dimensional genomic data-sets. Our group leads analyses of such data in consortia focused on Alzheimer’s Disease (AD) and related neurodegenerative disorders, including AMP-AD and MODEL-AD. We also work across disciplines to develop technologies that make these analyses available to a wide audience of researchers. Most notably, we recently celebrated the launch of Agora, an interactive, web-based explorer that provides access to research and analyses of nascent AD drug targets produced in conjunction with the NIH-led Accelerating Medicines Partnership.

Systems Biology

The Systems Biology research group at Sage Bionetworks is working to understand the underlying mechanisms causal to common disease. We use large-scale genomic analysis to identify disease subclasses, generate diagnostic and prognostic biomarkers, and to identify pathophysiology causal to disease in collaboration with academic and industry partners. Our current portfolio is focused on neurobiology, spanning both neurodegenerative and neuropsychiatric disorders, and includes projects in other disease areas including immunology, metabolic disease and craniofacial deformation.

Technology Platforms & Services

We’re working on the tools and platforms required to gather, share and use biomedical data in novel ways. These are targeted both at the research community, as well as organizations and individuals who are involved in providing data and being involved in the research process. They range from the technology platforms Synapse and BRIDGE, through novel methods of addressing governance issues around the distribution of human data such as E-Consent, to the ability to run Challenges to solve data-driven questions through our partnership with DREAM.