Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Monash University
- University of New South Wales
- The University of Queensland
- University of Sydney
- Curtin University
- Flinders University
- RMIT University
- La Trobe University
- RMIT UNIVERSITY
- UNIVERSITY OF SYDNEY
- FLINDERS UNIVERSITY
- Nature Careers
- Queensland University of Technology
- University of Adelaide
- CSIRO
- University of Southern Queensland
- University of Tasmania
- AUSTRALIAN NATIONAL UNIVERSITY (ANU)
- EDITH COWAN UNIVERSITY
- Macquarie University
- Murdoch University
- BOND UNIVERSITY
- Deakin University
- James Cook University
- LA TROBE UNIVERSITY
- Swinburne University of Technology
- THE UNIVERSITY OF NEWCASTLE AUSTRALIA
- The University of Newcastle
- The University of Western Australia
- UNIVERSITY OF MELBOURNE
- UNSW Sydney
- 21 more »
- « less
-
Field
-
PhD Scholarship Develop multimodal machine learning models to predict glioblastoma treatment outcomes using imaging and clinical data. Work with real-world data from John Hunter Hospital in a
-
materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
-
Machine learning has recently made significant progress for medical imaging applications including image segmentation, enhancement, and reconstruction. Funded as an Australian Research Council
-
" "Machine-learning-based imaging processing" webpage For further details or alternative opportunities, please contact: haoran.ren@monash.edu.
-
This Masters or PhD project aims to explain the uncertainty of Machine Learning (ML) predictions. To this effect, we must quantify uncertainty, devise algorithms that explain ML predictions and
-
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
-
Environmental Engineering Mechanical and Aerospace Engineering Electrical and Computer Systems Engineering Chemical and Biological Engineering Materials Science and Engineering About the Role We are seeking
-
, algorithmic methods, and machine learning approaches to advance research in melanoma and cancer biology. Specifically, you will support the major project “Predicting Early-Stage Melanoma at High Risk of
-
. Required knowledge Strong background in machine/deep learning, computer vision, or applied statistics. Solid programming skills in Python and experience with deep learning frameworks (e.g., PyTorch
-
Professorial Research Fellow in Artificial Intelligence (AI) and Machine Learning (ML) to provide leadership and vision in advancing research excellence. This is a unique opportunity to apply cutting-edge