Phd Research Summer Intern Ai/ml & Digital Health

Johnson & Johnson Innovative Medicine

London, United Kingdom
Self-supervised learning frameworks
Foundation models
Multimodal 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.
  • Johnson & Johnson Innovative Medicine Research & Development develops treatments that improve the health of people worldwide.

Matching Summary

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

Skills & Requirements

Must-have

  • self-supervised learning frameworks
  • foundation models
  • multimodal sensor data
  • deep learning for time-series
  • Python programming

Nice-to-have

  • wearable sensor data experience
  • physiological signal processing
  • digital health applications
  • transformers and contrastive learning

Key Requirements

  • PhD candidate
  • Machine Learning, AI, Computer Science, Biomedical Engineering, Signal Processing, or related quantitative fields
  • deep learning frameworks (PyTorch or TensorFlow)
  • large-scale datasets and research pipelines

Work Rights

Not specified

Tailored Resume

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