Johnson & Johnson

At Johnson & JnJ, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at As guided by Our Credo, Johnson & JnJ is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & JnJ, we respect the diversity and dignity of our employees and recognize their merit. Job Function: Career Programs Job Sub Function: Non-LDP Intern/Co-Op Job Category: Career Program All Job Posting Locations: London, United Kingdom, Paris, Île-de-France, France Job Description: Research Intern AI/ML & DH Data Science and Digital Health (DSDH) function within Johnson & JnJ Innovative Medicine Research & Development is seeking a PhD level Research Intern to support the development of foundation models for multimodal wearable sensor data, including accelerometer, PPG, ECG, and other physiological signals. The intern will work on self supervised and multimodal representation learning to build scalable models that generalize across digital health applications such as human activity recognition, sleep staging, cardiovascular monitoring, gait analysis, and digital biomarker discovery. Johnson & JnJ Innovative Medicine Research & Development develops treatments that improve the health of people worldwide. Research and development areas encompass multiple therapeutic areas (TA) including oncology, cardiopulmonary, immunology and neuroscience. Our goal is to help people live longer, healthier lives. We have produced and marketed many first-in-class prescription medications and are poised to serve the broad needs of the healthcare market, from patients to practitioners and from clinics to hospitals. To learn more about Johnson & JnJ Innovative Medicine R&D, please visit The AI/ML and Digital health team within Johnson & JnJ Innovative Medicine Research & Development is a part of Data Science & Digital Health (DSDH) function and develops innovative AI/ML and analytical solutions using a variety of data sources across multiple diseases and therapeutic areas. We are looking for an outstanding candidate for the Research Intern AI/ML & DH whose responsibilities include: Key Responsibilities Design and implement self supervised learning frameworks for wearable time series data. Train foundation models on large scale unlabelled multimodal sensor datasets. Develop architectures using transformers, contrastive learning, masked modelling, and cross modal attention. Integrate heterogeneous sensors (accelerometer, PPG, ECG, heart rate) using multimodal fusion strategies. Evaluate learned representations on downstream health tasks (HAR, sleep, stress, gait, health outcomes). Contribute to reproducible research outputs, including publications and well documented code. Required Qualifications PhD candidate in Machine Learning, AI, Computer Science, Biomedical Engineering, Signal Processing, or other related quantitative fields. Strong programming experience with Python and deep learning frameworks (PyTorch or TensorFlow). Strong technical background in deep learning for time series data and self supervised learning. Experience working with large scale datasets and research pipelines. Preferred Qualifications Experience with wearable sensor data and multimodal machine learning. Familiarity with transformers, contrastive learning, and masked modelling. Background in physiological signal processing and digital health applications. Exposure to time series foundation models or large scale model training. Required Skills: Preferred Skills:

A leading healthcare company in London is seeking a Research Intern in AI/ML to develop models for wearable sensor data. The ideal candidate will be a PhD candidate with experience in Python and deep learning frameworks, focusing on applications such as human activity recognition and cardiovascular monitoring. This role offers a unique opportunity to contribute to groundbreaking research and the advancement of digital health solutions.