Research Intern Ai/ml & Dh

Johnson & Johnson

Cambridge, Massachusetts, United States of America
$23.00ph to $51.50ph; not specified; medical benef...
Hybrid
Self-supervised learning for time-series data
Multimodal representation learning
Foundation models for sensor data
Support the development of foundation models for multimodal wearable sensor data, including accelerometer, PPG, ECG, and other physiological signals

Job Summary

  • Support the development of foundation models for multimodal wearable sensor data, including accelerometer, PPG, ECG, and other physiological signals.
  • Work on self-supervised and multimodal representation learning to build scalable models that generalize across digital health applications.
  • Contribute to reproducible research outputs, including publications and well-documented code.

Matching Summary

Support the development of foundation models for multimodal wearable sensor data, including accelerometer, PPG, ECG, and other physiological signals.

Salary

$23.00/hr to $51.50/hr; Not specified; Medical benefits, sick time, retirement plan

Skills & Requirements

Must-have

  • Self-supervised learning for time-series data
  • Multimodal representation learning
  • Foundation models for sensor data
  • Transformer architectures
  • Deep learning frameworks (PyTorch/TensorFlow)

Nice-to-have

  • Physiological signal processing
  • Digital health applications
  • Human activity recognition
  • Cardiovascular monitoring
  • Wearable sensor data experience

Key Requirements

  • Currently pursuing a PhD
  • Completion of Undergraduate Freshman year
  • Cumulative GPA of 2.8 or higher
  • Strong programming experience with Python
  • Permanently authorized to work in the U.S.

Work Rights

Permanently authorized to work in the U.S.

Tailored Resume

Cover Letter