Machine Learning Scientist Intern

Primary Function of Position

Contribute broadly to the Advanced Product Development team, responsible for machine learning, advanced analytics, and new technology development focused on surgical workflow and performance for next generation robotic surgery platforms.

The successful candidate must excel in a high-energy, focused, small-team environment, be able to initiate and drive new research and development directions. A strong sense of shared responsibility and shared reward is required.

Essential Job Duties

• Exploration and development of machine learning algorithms for spatiotemporal analysis, including multiclass classification, clustering, temporal segmentation, sequence labeling, spatial segmentation, and 3D reconstruction.
• Development of new technologies and digital products to improve surgeon and team performance on robotic surgery platforms.
• Contributing to multiple areas of research, including but not limited to the following:
  • Designing and applying machine learning algorithms to novel, surgical applications
  • Characterizing surgeon and team behavior and workflow to optimize new technologies
  • Fully integrating machine learning into core digital products and intelligent systems
  • Conducting user studies to evaluate digital product concepts
  • Presenting research at international conferences and publishing research in top academic journals

Required Skills and Experience

University Hiring Program Eligibility Requirements:

• University Enrollment: Must be currently enrolled in and returning to an accredited degree-seeking academic program after the internship.
• Internship Work Period: Must be available to work full-time (approximately 40 hours per week) during a 10-12 week period starting May or June. Specific start dates are shared during the recruiting process.

Required Education and Training

• Current enrollment in Computer Science, Statistics, Applied Mathematics, Robotics, Neuroscience or engineering related degree-seeking program at the Doctorate level
• Demonstrate excellent communication skills both written and verbal
• Interested in early research and development through to product roll-out
• Solid understanding of statistics, machine learning, and deep learning algorithms and techniques is required
• Experience with sequence modeling, image analysis, activity recognition, temporal segmentation, spatial segmentation and/or 3D reconstruction on real-world data is required
• Experience with Python is required
• Hands-on experience with deep learning frameworks such as TensorFlow and/or PyTorch is required
• Hands-on experience with CNNs, RNNs, LSTMs, and attention-based architectures is required

Preferred Skills and Experience

• Hands-on experience leveraging foundation models (Dino, SAM, DepthAnything, VLMs, and/or LLMs) is strongly preferred
• Experience with data visualization is a plus
• Experience with R, SQL is a plus
• Experience with clinical studies is a plus