Sage Bionetworks is currently recruiting for a scientist with experience in 
remote sensors, signal processing and/or machine learning.  We are actively 
running clinical studies that use wearable sensors and smartphones to 
quantify symptoms of disease and health.  You would be joining a team of 
computational scientists, software engineers and clinicians to analyze data 
from thousands of patients and to help design new tests to be incorporated in 
future studies using smartphones.

About you: You have a background in electrical engineering, biomedical 
engineering, computer science, statistics, bioinformatics or related 
computational fields.  You have experience working with time series data in 
measuring biological processes such as accelerometers, force plates, heart 
rate monitors, etc.  

Specific Responsibilities Include

1. Design new modules for measuring phenotypes using sensors embedded in a 
smartphone (accelerometer, gyroscope, pressure sensors, microphone, etc).
2. Extract features from sensor data and apply supervised and unsupervised 
machine learning methods to quantify disease.
3. Create web-accessible analyses that are reproducible and re-usable.
Work with our software team that builds mHealth applications to drive new 
experiments.
4. Automate the execution of new analysis methods using scripting and 
statistical programming.

Basic Qualifications
1. A graduate degree in a quantitative field such as EE, BME, applied math, 
CS, bioinformatics etc.
2. Signal processing experience.
3. Experience working within a team of biologists, statisticians and software 
engineers to compile, format, and analyze large, high-dimensional data sets 
for downstream analysis.

Additional Skills/Preferences
1. Software development experience, including strong programming skills in a 
high level language (especially Python, R or Matlab).
2. Experience with Linux shell scripting and running distributed analyses.
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 remote sensor data sets. To enhance collaborative 
efforts, we provide a collaborative compute platform (www.synapse.org) for 
sharing research insights in a transparent, reproducible fashion and bridge 
for collecting data from mHealth applications.

To apply for this position, please send your CV and cover letter to: 
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