Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
Communities, and Geopolitical Security – Monash is where impact begins. Join an environment that values curiosity, collaboration, and capability. Be part of a team that’s inclusive, diverse, and driven to make
-
of Information Technology is seeking a Level A Research Fellow to join the Department of Data Science and Artificial Intelligence (DSAI). This role offers an exciting opportunity to contribute to cutting-edge research
-
The world is dynamic, in constant flux. However, machine learning typically learns static models from historical data. As the world changes, these models decline in performance, sometimes
-
gases" "Ultrafast dynamics of quantum matter" "Interactions between strongly coupled light-matter quasiparticles" "Atomically thin materials coupled to light" "Periodically driven many-body systems" web
-
Machine learning, dynamical systems theory, control theory, signal processing, network theory, neuroscience are all relevant and a student should have strong knowledge in at least one of these and a
-
Advisory System, or data from other implantable or wearable devices. This involves consideration of both feature-based machine learning or data science approaches and neural mass parameter estimation
-
while inferring underlying physiological changes. Required knowledge Machine learning, dynamical systems theory, control theory, signal processing, time series analysis, neuroscience are all relevant and
-
The goal of my research is to synthesize and characterize low-dimensional nanomaterials with atomic-scale precision and tailored electronic, optoelectronic, magnetic and chemical properties. In my
-
is your gateway to success. Total scholarship value Up to $6,000 Number offered Two See details Matthew J.L. Chung Kai Shing Monash International Merit Scholaship I am happy and honoured to leverage
-
‘dynamic graphs’. Although recently many studies on extending deep learning approaches for graph data have emerged, there is still a research gap on extending deep learning approaches for identifying