Phd Research Summer Intern Ai/ml & Digital Health

J&J FAMILY OF COMPANIES

London, United Kingdom
Self-supervised learning frameworks
Foundation models for time-series data
Deep learning for time-series 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.

Skills & Requirements

Must-have

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

Nice-to-have

  • wearable sensor data experience
  • physiological signal processing
  • digital health applications
  • time-series foundation models

Key Requirements

  • PhD candidate
  • Machine Learning, AI, Computer Science, Biomedical Engineering, Signal Processing, or related quantitative fields
  • Strong programming experience
  • Strong technical background
  • Experience with large-scale datasets

Work Rights

Not specified

Tailored Resume

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