Sort by
Refine Your Search
-
Machine Learning”). Working closely with Dr. Clement Canonne and his team, the successful candidate will develop and analyse new differentially private algorithms for distributed statistical inference, and
-
collaborator with the aim to use machine learning/AI approaches in combination with commercial multispectral and hyperspectral remote sensing platforms to perform within-field mapping of weeds and disease in
-
) at the University of Sydney. The ACFR is one of Australia’s leading robotics research groups, and the Robotic Imaging Lab is focused on endowing machines with new ways of seeing the world. We are expanding our team
-
literacy with a good knowledge of relevant computer programs, and ability to work across and connect these as needed. Desirable criteria – you may have (or be willing to learn) the ability to write research
-
, control, stochastic optimisation, power grid design, and statistical analysis. The project aims to use state-of-the-art optimisation, control, machine learning, mine planning, and power engineering
-
theoretical chemistry needed to map chemical problems onto quantum machines. For further information, please see our website, https://www.kassal.group , or contact Prof. Kassal. You will have access to the rich
-
of Professor Geordie Williamson at SMRI. The successful applicant will undertake research in either modular representation theory, or the use of machine learning techniques in pure mathematics research
-
statistical models and reproducible data processing pipelines with experience of best practices in modern statistical methods, including e.g. latent variable modelling, data reduction, machine learning, and
-
of Western Australia develop resource-efficient quantum characterisation, verification, and validation by leveraging insights from the fields of robotic control and machine learning, e.g., link develop novel
-
, Social Sciences, Political Sciences, Computer Sciences, or Engineering, with a strong track record (relative to opportunities) in research on disaster management, extreme contexts, and resilience including