15 phd-studenship-in-computer-vision-and-machine-learning Fellowship positions at University of Adelaide
Sort by
Refine Your Search
-
/research/about-us/ AIML is the largest University based computer vision and machine learning research group in Australia, with over two hundred members including academics, engineers, research staff and
-
-based health care. High level interpersonal, communication and organisational skills. Ability to contribute to a diverse and collaborative team environment. Commitment to ongoing learning. Level B: PhD in
-
, epigenetics, development, and cell biology to lead and contribute to cutting-edge research. To be successful you will need: A PhD in Cell Biology, Molecular Biology, Genetics, Biochemistry, or a related area
-
need: A PhD in epidemiology, public health, medical sciences or other areas relevant to primary health care Demonstrated experience contributing to the coordination of quantitative health research
-
This PhD scholarship is funded by an Australian Research Council Industry Fellowship grant. It is a 3.5-year research training program. The ARC Industry Fellowship program aims to develop a strong
-
at the University of Adelaide, contributing to cutting-edge research in computer vision and machine learning for space applications. This role focuses on advancing machine learning and computer vision research, with
-
learning research and development, particularly with a specialisation in such areas as: digital forensics, computer vision, biometrics (face or voice recognition, etc.) and natural language processing
-
actions working on causal AI for a changing world. The AIML at the University of Adelaide is the largest computer vision and machine learning research group in Australia with over 180 members including
-
will need: A PhD or equivalent in stochastic modelling, data science, network analysis, statistics, or related discipline Is eligible to apply for an Australian Government security clearance. Research
-
to contribute to the development of management strategies for these pests. The ideal candidates will have a PhD in agricultural entomology or closely related field and interest in advancing knowledge that will