81 machine-learning-"https:"-"https:"-"https:" "Computer Vision Center" Postdoctoral research jobs in Australia
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machine/deep learning, computer vision, or applied statistics. Solid programming skills in Python and experience with deep learning frameworks (e.g., PyTorch or TensorFlow) Project funding Other Funding
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ultimately shifts in species' distributions. This project harnesses research in ecological and agent-based modelling, machine learning, and AI to increase the predictive power of models of species
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Faculty of Engineering, Architecture and Information Technology / School of Electrical Engineering and Computer Science Full-time fixed-term position for up to 12 months Base salary will be in the
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skills in video-based behavioural analysis and/or applying computer vision or machine learning methods to biological data. Applicants should have good working knowledge of experimental design for welfare
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MACQUARIE UNIVERSITY - SYDNEY AUSTRALIA | North Ryde, New South Wales | Australia | about 1 month ago
machine learning, linear logic, etc.).While the position start date is flexible, the successful applicant must have completed their PhD prior to commencing the role. The position can commence at any
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mathematics (such as for differential geometry, algebraic geometry, etc.) or for computer science (such as machine learning, linear logic, etc.). While the position start date is flexible, the successful
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(such as machine learning, linear logic, etc.). While the position start date is flexible, the successful applicant must have completed their PhD prior to commencing the role. The position can commence
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effectively within a multidisciplinary research environment. Experience with quantitative genetics, Bayesian methods, machine learning, large-scale genomic datasets, single-cell omics or integrative
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management systems, workflows and research infrastructure. Apply advanced statistical, machine learning and data engineering methodologies to large-scale, longitudinal datasets, contributing to
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cutting-edge bioinformatics, AI, machine learning, and multi-omics technologies to drive discoveries that have the potential to transform cancer diagnosis, treatment, and patient outcomes. This is an