202 phd-studenship-in-computer-vision-and-machine-learning positions at University of Adelaide
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
to detail, sound judgement, initiative and confidentiality. Advanced computer skills using the Microsoft Office Suite of products, particularly Excel. The path to Adelaide University We are on an exciting
-
group of PhD researchers who will tackle the most pressing questions in Machine Learning while ensuring AI serves humanity responsibly. You'll work within one of our specialised research themes, each
-
methods for provable network security. The School of Computer and Mathematical Sciences is recruiting a research fellow to work on next generation network security technologies. Join a world-class research
-
Family Foundation. The scholarships are intended to supplement an existing Australian Government Research Training Program Stipend Scholarship (RTPS) or similar institutional PhD stipend scholarship
-
). Proficiency in numerical modelling, data analysis and instrument control in languages such as Matlab, Python, C/C++, etc. Familiarity with sensor technologies and applications, machine learning, and electronics
-
The Adelaide Graduate Research School is partnering with the Borderline Personality Disorder Collaborative to provide a research internship opportunity for a PhD student. The Borderline Personality
-
ambitious research program to investigate the intersection of plate tectonics, critical metals, and Earth's habitability by trying to better model the Earth’s surface evolution from 1800–500 million years ago
-
plays a key role in supporting and advancing the research and strategic goals of the Australian Institute for Machine Learning. This position bridges research development and strategic operations, guiding
-
focused on understanding and countering harmful narratives and, mis/disinformation, and applying social network analysis. To be successful you will need: PhD in a relevant discipline such as computer
-
engineers to transform raw imaging and spectral data into meaningful, actionable insights. The role focuses on developing and optimising data pipelines, applying advanced statistical and machine learning