Machine Learning Intern

at  Prenuvo

ABOUT US

At Prenuvo, we are on a mission to flip the paradigm from reactive “sick-care” to proactive health care. Our award-winning whole body scan is fast (under 1 hour), safe (MRI has no ionizing radiation), and non-invasive (no contrast). Our unique integrated stack of optimized hardware, software, and increasingly AI, coupled with the patient-centric experience of our clinics across North America, have allowed us to lead the charge against “we caught it too late again.” Prenuvo operates preventative screening clinics in Vancouver, Silicon Valley, Dallas, Boca Raton, Minneapolis, Los Angeles, New York City, Bethesda, Chicago, and Atlanta, with more clinics in North America and internationally in the next 2 years.
We are looking for Machine Learning Interns to join the AI Team. We are looking to hire 5-6 interns who will work from our Headquarters located at 1290 Homer Street, Vancouver BC, V6H 1E1. This is a contract position, the length of the internship period is 8 months.
Help reshape the world through proactive healthcare while working with cutting-edge technology and high performing teams with deep expertise - join us to make a difference in people’s lives! We are looking to hire

WHAT YOU’LL DO

• Anatomy and MRI Acquisition: Learn the basics of human anatomy and the fundamentals of MRI acquisition to understand the context and significance of the medical images.
• Exploratory Data Analysis: Perform exploratory data analysis (EDA) on our collection of MR images to identify patterns, anomalies, and insights that can inform model development.
• Literature Review: Conduct a thorough review of current state-of-the-art approaches in machine learning, focusing on segmentation and classification problems relevant to medical imaging.
• Model Development: Train machine learning models to address specific tasks such as image segmentation and classification, using our extensive dataset of MR images.
• Model Deployment: Assist in deploying machine learning models to production, ensuring they are scalable, efficient, and integrated with existing systems.
• Documentation: Document processes, experiments, and outcomes clearly and concisely to ensure reproducibility and knowledge sharing within the team.
• Collaboration: Work closely with data scientists, engineers, and other stakeholders to understand requirements and deliver solutions that meet business needs.
• Research: Stay updated with the latest advancements in AI/ML technologies and contribute ideas to enhance our projects.