Data analysis to enable improved real-time alarms and clinical decision support in the cardiac operating room
About The Role:
VA Boston is accepting applications for post-masters or post-doctoral fellows who are interested in advancing surgical team communication, smart alarm systems, clinical decision support, and closed-loop control of medical devices to improve patient safety and outcomes in the cardiac operating room. You will work with clinicians and scientists from the VA Boston, Massachusetts General Hospital, and Harvard Medical School to analyze in house and publicly available data sets of electrocardiograms (ECGs) with the goal of developing and validating novel metrics, alarms, and closed-loop systems based on heartrate variability (HRV) metrics. This position is for a one-year term with possible extension for a second year.
About The Team:
This position will work closely with the Cardiac Surgery program at the West Roxbury VA Hospital and the Medical Device Plug-and-Play Program (MD PnP) at Massachusetts General Hospital. In previous work, we have collected clinician HRV data and analyzed it for correlations with cognitive load, interruptions, and other events during surgery. You will work with us to further study correlations of various metrics with events of interest and develop real-time monitoring algorithms that can make use of HRV data to inform smart alarms, checklists and other clinical decision support systems, and other clinical algorithms.
What You’ll Be Doing
Depending on your interests and skill set you may have the opportunity to work on:
- Continue ongoing research involving the development of real-time calculation of HRV metrics,
event detection, and correlation with other events
- Maintain and improve the existing data repositories including writing scripts for pre-processing and format translation
- Create new data analysis tools in C++, Python or Matlab to integrate with existing statistics and machine learning packages
- Research and integrate existing HRV analysis tools and creating workflows to automate processing of medical data to extract HRV metrics, compare results from various existing and new tools, and examine correlations with other recorded events
- Together with the team, evaluate and fill gaps in the process
- Publish original research in peer reviewed journals.
- Aid in supervision of undergraduate, graduate, and medical students
Qualifications, Skills, and Competencies
We are seeking strong communicators with a passion for research, improving surgical processes and patient outcomes, and an interest in leveraging data analysis towards these goals. Some of the primary skills and competencies that we are looking for include:
- An ideal candidate would have 2+ years of experience working in clinical research or with large-scale data at any level.
- Exceptional written and verbal communication skills
- Eager to learn new tools and methods
- Great teamwork skills balancing working on projects independently while also collaborating with the team to solve problems
- A self-starter – able to set schedules, manage deadlines and risks to deliver on assigned projects
- Excellent planning, organizational and time management skills
Assets for this position:
- 1+ years of experience developing in Python, with a working knowledge of machine learning and related tools and platforms and statistics.
- A Masters or PhD in Computer Science, Biomedical Engineering, Mathematics, Computer Engineering or related industry experience.
If interested, please send your CV to Annette Phillips at email@example.com with the subject line “BD-STEP Application”. If you have any additional questions, feel free to reach out to Trevor Michelson at firstname.lastname@example.org for more information