View job on Handshake
Dexcom, Inc. empowers people to take control of diabetes through innovative continuous glucose monitoring (CGM) systems. Headquartered in San Diego, California, Dexcom has emerged as a leader of diabetes care technology. By listening to the needs of users, caregivers, and providers, Dexcom simplifies and improves diabetes management around the world.
Throughout the pandemic, one of our key priorities has been to keep employees as safe as possible. At this time, we plan for most of our summer internships to be virtual, with exceptions of essential groups. We ask for our intern candidates to be flexible to a virtual format or residence in the location of the position throughout the duration of the internship.
Tasks to be performed:
- Develop and optimize mathematical model to illustrate physiology process around glucose sensor;
- Develop and optimize empirical model or machine learning model to improve event detection and glucose estimation;
- Develop feasible solution to optimize model parameters retrospectively or prospectively;
- Perform comprehensive data analysis and data mining to inform feature generation and model selection.
- Run simulation and evaluate the outcome
- Prepare results and present a summary of results to technical and non-technical audience.
Essential Duties and Responsibilities:
- Perform data mining
- Time series, machine linear and mathematical Modeling
- Run simulation
- Perform data analysis including evaluation and root cause analysis
- Generate report and technical review
- PhD or Master’s student in mathematics or Statistics related area;
- Understand, review, and implement research papers from scientific journals
- Programming languages such as MATLAB, Python or R;
- Sound understanding of statistics and machine learning techniques;
- Experience in mathematical modeling for physics/chemical/physiology process.
- A master or Ph.D. degree in Mathematics or Statistics related area;
- Good understanding of analog and digital signal processing techniques preferred;
- Medical device experience preferred.
Training or education required to perform: