PhD in Generative AI for Mobile and Digital health

PhD in Generative AI for Mobile and Digital health 3 weeks ago Be among the first 25 applicants The Ubiquitous Internet Unit of IIT-CNR (Pisa, Italy) is seeking highly motivated university graduates (or that will graduate by next October 2025) with a strong academic background who are interested in pursuing a PhD in Generative AI for Mobile and Digital health . Candidate profile The candidate must have (or be about to obtain) a Master’s degree (or equivalent) in Computer Science, Computer Engineering, Biomedical Engineering, Mathematics, or a closely related field. An excellent academic record is required, with outstanding marks in subjects such as machine learning and artificial intelligence. Technical Skills The following skills are an advantage for the candidate: Experience with ML and deep learning frameworks Proficiency in Python PhD topic The generation of synthetic mobile sensor data is a critical challenge for advancing machine learning applications in health monitoring, human activity recognition, and edge AI systems. Traditional approaches, such as GANs and VAEs, have demonstrated success in generating realistic sensor data but often struggle with temporal consistency, multimodal coherence, and personalization. Recent advancements in Large Language Models (LLMs) offer new opportunities for generative tasks, yet their ability to model structured time-series data remains under-explored. The research challenges addressed by this PhD include (but are not limited to) the investigation of LLMs potentialities in the generation of synthetic multimodal sensor data, exploiting also the possible integration with other generative models (GANs, Diffusion Models, and Transformer-based architectures) to enhance realism, efficiency, and privacy. The study will explore: (1) baseline performances of LLMs on sensor data generation (2) new solutions to improve temporal consistency and multimodal integration (3) optimization of model efficiency for on-device and federated deployment (4) privacy preservation The study plan will include the validation of the synthetic sensor data in real-world machine learning applications in the m-health domain, such as stress detection, physical activity recognition, and digital health analytics. Seniority level Seniority level Entry level Employment type Employment type Full-time Job function Job function Research Industries Research Services Referrals increase your chances of interviewing at IIT-CNR by 2x Get notified about new Masters Student jobs in Pisa, Tuscany, Italy . We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI. J-18808-Ljbffr

Location: provincia-di-pisa, IT

Posted Date: 5/12/2025