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## Department Overview
We are developing some of the first in-human AI-powered algorithms to transform care for pregnant women at risk for adverse outcomes. There are multiple events around the time of delivery that can affect the outcome and experience for both the mother and infant. Our lab is focused on creating critical cutting-edge future-forecasting and vitals-management algorithms to improve patient safety, predict and prevent adverse pregnancy outcome.

## Job Description
We are looking for a responsible, motivated, and self-directed machine learning intern who is interested in applying statistical, machine learning, and deep learning approaches to obstetric anesthesia research projects. You will work with the Senior Machine Learning Scientist to develop algorithms that run on data in our in-house machine learning data repository. Proficiency in Python is a must, and experience with TensorFlow and NLP is beneficial. Attention to detail, high integrity, and excellent communication skills are a must.

## Minimum Qualifications
* Proficiency with Python3
* Experience with NumPy, SciPy, Tensorflow, and/or PyTorch
* Experience with Jupyter Notebook
* Experience with interacting with CSV data with both Python and programs like Excel
* Good communications and organization skills
* Excitement to learn and apply new techniques

## Responsibilities
Write Python code to implement and test new theories and models.
* Write code to analyze both medical records and waveform data.
* Run summary statistics to understand data and cohorts.
* Create visualizations to aid in interpreting data and results.
* Document and version control code.
* Participate in lab-group and ML-team meetings.

  • The candidate must be available to work part-time 6- 8 months.
  • The start date may be flexible, ideally by September 1.
  • Hiring is pending upon credentialing from our institution, a process that may take 6 weeks or longer.
  • There is an opportunity for hiring on a permanent position.