Research Data Analyst
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The Research Data Analyst will work under the direction of Co-Directors of the Center for Biosignal Research (CBR) and report directly to the CBR Scientific Program Manager. The CBR at UCSF focuses on the study and clinical use of biosignals, or signals that can be continuously measured and monitored from the human body. Our areas of research broadly focus on improving biosignal analysis through signal processing and advanced algorithms, identifying predictors of adverse outcomes, using biosignals to improve physiologic understanding and leveraging these insights to improve patient care and reduce false alarms in bedside monitoring.
The ideal candidate will leverage their experience with complex data analysis, in particular time-series data analysis, biomedical/clinical informatics, and/or signal processing, to develop and evaluate algorithms to interpret continuous bedside monitoring data, integrating additional clinical data such as electronic medical records when appropriate. Prior experience with clinical or biosignal data is preferred but not required. Example projects include the development of algorithms to improve alerting systems for clinically significant arrhythmias and other events, using monitoring data to predict patient trajectories within specific disease cohorts, or assessing the impact of changing alerting mechanisms on overall alarm burden in retrospective data. There are also opportunities to contribute to the design and implementation of the data and computing infrastructure that underlie these efforts. The incumbent will work independently and in collaboration with CBR staff and faculty investigators to facilitate multiple research projects and CBR efforts.
The ideal candidate will leverage their experience with complex data analysis, in particular time-series data analysis, biomedical/clinical informatics, and/or signal processing, to develop and evaluate algorithms to interpret continuous bedside monitoring data, integrating additional clinical data such as electronic medical records when appropriate. Prior experience with clinical or biosignal data is preferred but not required. Example projects include the development of algorithms to improve alerting systems for clinically significant arrhythmias and other events, using monitoring data to predict patient trajectories within specific disease cohorts, or assessing the impact of changing alerting mechanisms on overall alarm burden in retrospective data. There are also opportunities to contribute to the design and implementation of the data and computing infrastructure that underlie these efforts. The incumbent will work independently and in collaboration with CBR staff and faculty investigators to facilitate multiple research projects and CBR efforts.
Required Qualifications
- BS in related field and 2+ years of experience, or equivalent experience / training
- Thorough knowledge of at least one of Python, Java, C++, or related
- 1+ years of experience with time-series data analysis
- 1+ years of experience with signal processing methods and/or biomedical/clinical informatics
- 2+ years of experience with data science, including statistical analysis, data transformations, and visualization
- Advanced ability to communicate complex information in a clear and concise manner both verbally and in writing
Preferred Qualifications
- Advanced degree in related field
- Knowledge of HPC/cluster computing
- Experience with clinical data
- Track record of peer-reviewed research publications
- Experience with software engineering best practices
- Experience with SQL and/or noSQL databases