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Criteria. For a confidential discussion regarding this role, please contact Nolene Bryne (Associate Professor, Circular Design) on nolene.byrne@deakin.edu.au For a copy of the position description, please
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available for two years. Keywords: Geometric Deep Learning, in particular Graph Neural Networks, Deep Reinforcement Learning, Generative Modelling, in particular Denoising Diffusions, Combinatorial
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. Proficiency in deploying and managing wildlife camera‑trap networks and processing large image datasets. Experience developing and validating machine‑learning and AI models for image object detection and
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this role, please contact Max Kelly (Associate Professor, International and Community Development) via max.kelly@deakin.edu.au For a copy of the position description, please see below: Level-B---Research
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We are seeking a Senior Research Fellow (Clinical) to lead research that supports the co-design, implementation, and evaluation of innovative, multidisciplinary team (MDT)-based primary care models
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collection methods. You’re skilled in developing computational models and deep neural networks that reflect principles of human cognition and brain function. Your academic record includes high-quality peer
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frameworks, such as PyTorch (preferred) or TensorFlow, with a preference for experience implementing SOTA models and training procedures from academic journal papers. Development of data engineering pipelines
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origami synthesis and characterisation. Previous experience with non-academic and industry projects is desirable. Demonstrated expertise in supramolecular chemistry, computational modelling, and/or
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SRH’s Program 1 (Process Integration and Sustainability) and undertake a new research activity under Project 1.2.4 – Numerical Modelling of Electric Smelting Furnace Phenomena: Melting of Direct Reduced
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tools to tackle some of the most complex questions in brain science. As a Level A research-only academic, you will contribute to projects that integrate computational models with experimental neuroimaging