Sort by
Refine Your Search
-
Listed
-
Field
-
analysis, contextual analysis, audio feature extraction, and machine learning models to identify and assess potentially dangerous content. Similarly, computer vision models are implemented to analyse images
-
David Shugg Professionalism Scholarship Industry Leaders Scholarship This Scholarship is to honour the important role that David Shugg played in the professionalism of paramedics. Throughout David’s career, he advanced and embedded professionalism in paramedic training and education in the...
-
to vital organs caused by disease, injury, or genetic conditions. The Institute operates within a highly collaborative ecosystem, engaging with Monash Institute for Medical Engineering (MIME), the Biomedical
-
schools as part of the Access Monash Mentoring Program, giving you the opportunity to develop your leadership, public speaking and teamwork skills. The Gandel family have a close connection with Monash
-
, the focus of this role will be to provide a range of professional and high-quality administrative services to support the effective operation of the School of Clinical Sciences. As the successful
-
Planning is the reasoning side of acting in Artificial Intelligence. Planning automates the selection and the organisation of actions to reach desired states of the world as best as possible. For many real-world planning problems however, it is difficult to obtain the full model of the world...
-
Experience in developing and deployment of iOS and Android applications, APIs, or standalone desktop applications Experience working with Artificial Intelligence, Machine Learning or data science software
-
., Pan, S., Aggarwal, C., & Salehi, M. (2022). Deep learning for time series anomaly detection: A survey. ACM Computing Surveys.
-
We are excited to offer a fully funded PhD position at the Faculty of Engineering, Monash University (Australia). This project focuses on developing new algorithms to equip social robots with
-
This PhD project is part of a larger project that aims to explain the uncertainty of Machine Learning (ML) predictions. To this effect, we must quantify uncertainty, devise algorithms that explain ML predictions and their uncertainty to different stakeholders, and evaluate the effect of the...