Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
, machine learning, remote sensing and silviculture to transform and upscale forest phenotyping operations. The role will be supervised by Dr. Mitch Bryson, who currently leads the Forestry Research group
-
and publications, will be key to your success in this role. You will also have: A PhD in computer science or closely related discipline; A record of high-quality algorithmic research in machine learning
-
), psychophysical methods, computational neuroscience methods, machine learning and modelling. Our studies utilise various haptic devices, and mechanical and electrical stimulators. Key skills required: PhD
-
statistical modelling such as machine learning methods and demonstrated experience in the handling and analysis of big data would be highly desired. The successful applicant will also demonstrate personal
-
in Deep Learning Theory who has: a PhD in mathematics, applied mathematics, data science, or a related area an excellent track record of publishing high-quality papers on deep learning theory, machine
-
looking for a Postdoctoral Research Associate in Deep Learning Theory who has: a PhD in mathematics, applied mathematics, data science, or a related area an excellent track record of publishing high-quality
-
partners and stakeholders use mechanistic modelling to spatialise crop yield predictions under a variety of data input scenarios use data-driven models and machine learning to better understand the spatio
-
licence is essential. Car ownership is desirable. To learn more about this position, and view the comprehensive skills and criteria list, a copy of the Position Description can be found by clicking
-
Accuracy in Algorithmic Machine Learning"). Working closely with Dr. Clement Canonne and his team, the successful candidate will develop and analyse new differentially private algorithms for distributed
-
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