-
activity, sleep and health behaviour change Project Description: Digital behaviour change tools reach large populations cheaply, but most deliver generic advice and lose their users within weeks. Large
-
datasets with different configurations (e.g., number of channels, sampling frequency and resolution). To leverage large-scale self-supervised learning to train models on unlabeled EEG data, reducing reliance
-
social media and online platforms. The project will use natural language processing (NLP), large language models (LLMs), and network analysis to identify coordinated harassment, anti-gender equality
-
infrastructure, public safety and smart environments. The successful candidate will be supervised by Dr Deval Mehta within the Department of Data Science & AI, Faculty of Information Technology, Monash University
-
someone with strong quantitative skills and an interest in using data to answer policy relevant research questions. The successful applicant will work with large administrative and survey datasets and apply
-
. Analysis of this data will employ both qualitative and quantitative methods. Work on WP-2 will suit someone with an interest and aptitude for coding administrative data using large language models. It will
-
14 Sep 2026 Beating to a different drum: the hidden rhythms shaping heart rate University of Melbourne researchers working on a large study of smartwatch data have found that the heart rates of 70 per
-
challenging for clinicians and pregnant women. Digital health records, advances in big data, machine learning and artificial intelligence methodologies, and novel data visualisation capabilities have opened up