Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- The University of Queensland
- UNIVERSITY OF WESTERN AUSTRALIA
- University of New South Wales
- The University of Western Australia
- University of Sydney
- Monash University
- University of Adelaide
- Curtin University
- Macquarie University
- RMIT University
- Flinders University
- James Cook University
- Australian National University
- FLINDERS UNIVERSITY
- AUSTRALIAN NATIONAL UNIVERSITY (ANU)
- MACQUARIE UNIVERSITY - SYDNEY AUSTRALIA
- UNIVERSITY OF ADELAIDE
- CURTIN UNIVERSITY
- Deakin University
- Federation University Australia
- QUEENSLAND UNIVERSITY OF TECHNOLOGY (QUT)
- THE UNIVERSITY OF NEWCASTLE AUSTRALIA
- UNIVERSITY OF SYDNEY
- University of Tasmania
- 14 more »
- « less
-
Field
-
postgraduate qualification in one of these fields plus relevant research experience. Demonstrated track record in epidemiological research with outcomes of high quality and high impact with clear evidence of
-
Australian National University | Canberra, Australian Capital Territory | Australia | about 2 months ago
, approximate inference, deep learning, or Bayesian optimisation are encouraged to apply. Interpretable Machine Learning for Natural Language – Led by Prof Lexing Xie, this stream applies machine learning
-
AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 2 months ago
deep learning theory and practice. Applicants with expertise in probabilistic modelling, approximate inference, deep learning, or Bayesian optimisation are encouraged to apply. Interpretable Machine
-
engineering and a strong foundation in data science. You bring a passion for solving complex problems and a track record of research excellence in optoelectronic materials, machine learning, or related fields
-
the timing, scale, and rate of mammal declines in Australia. They will use critical inferences of past demographic change and high-performance computing to disentangle the ecological mechanisms that were
-
statistical, Bayesian, and deep-learning approaches. Lead improvements in data quality, integration, and reproducibility across multi-centre trials and registries. Collaborate with leading clinicians, engineers
-
to engage with multidisciplinary teams and external partners. Desirable attributes include experience with spatio-temporal models, machine learning, Bayesian methods, and knowledge of environmental exposure
-
networks and/or probabilistic graphical models; and causal inference. An outstanding publication record in top tier machine learning and/or computer vision conferences or journals, commensurate with
-
learning and one or more of the following: transformer networks, implicit neural functions, graph neural networks and/or probabilistic graphical models; and causal inference. • An outstanding publication
-
and RCSWA students participating in service learning projects. Identify educational and upskill opportunities for RCSWA staff and students, track, evaluate and promote student involvement in research