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related field experience in the development of machine learning models using Python and pytorch expertise in two or more of the following technical areas: design of FPGA-based accelerators, high-level
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applications of data science and modelling. The successful candidate will support the research of Professor Lucy Marshall, Faculty of Engineering and will collaborate with members of her cross-institutional
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of the postdoctoral researcher will include: To work closely and proactively with Prof Anton van den Hengel to scope and develop research ideas. To develop algorithms, machine learning models, Python modules
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ideas. To develop algorithms, machine learning models, Python modules, demonstrators and training pipelines for publication and translation into commercial products that can be widely and reliably adopted
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cellular biology laboratory work, providing scientific support to an NHMRC funded project in a mouse model acute lung injury and a collaborative microbiome project in stool samples collected from patients
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ability to work with complex model systems both in vitro and in vivo. Evidence of contribution towards research relevant to the field of study/interest, such as publications, conference presentations
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how control parameters (e.g. bucket speed, size, depth, and packing density) influence energy dissipation develop mathematical models to predict and explain these effects collect and analyse data
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to: conduct high-quality research in relevant project areas undertake project-wide data and sample analysis, synthesis and curation, and assist CIs with overall project coordination lead the preparation of peer
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Postdoctoral Research Associate - Coral Reef Systems on the Edge, your key responsibilities will be to: conduct high-quality research in relevant project areas undertake project-wide data and sample analysis
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density) influence energy dissipation develop mathematical models to predict and explain these effects collect and analyse data, including with the use of machine learning use this knowledge to design