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approaches to model uncertainty for learned computer vision systems, including dense prediction. The position will develop novel methods for deep learning in computer vision that accurately quantify their own
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graduate with its Juris Doctor for admission to practice recognised as a high-level qualification in Australia and beyond. Coupled with the unrivalled excellence of the Melbourne Law Masters and its
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developing and implementing algorithms for processing, imaging or inversion of seismic data, preferably using MATLAB and/or Python. Experience or demonstrated ability in processing and analysis of surface
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journals. Prototype electrochemical devices based on research results. Undertake additional research responsibilities within the field of expertise. Actively apply for external grants and fellowships with
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to the safe and efficient operation of research equipment, infrastructure, methodologies and protocols Contribute to the upkeep of the project website and ensure safe handling and disposal of research materials
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expertise in digital imaging technologies and data-driven research solutions. Apply for and manage competitive research funding, including joint projects with colleagues. Supervise and mentor Honours and
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supporting a diverse range of imaging and analytical instrument platforms. About the opportunity Elaborate new methodologies applied to critical mineral research with a focus on REE and Li Identify efficient
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) GRADE 7, £39,355 - £45,413 pa Fixed-term Ref: 095593 A Research Fellow position is available in the group of Professor M. J. Rosseinsky OBE FRS to work in a team of computer scientists and materials
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lining the gut and lungs works to sense and trigger immune cells to drive effector and repair functions. Characterisation experiments will include ELISA, PCR, multicolour flow cytometry, imaging, cutting
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below or contact Dr. Erica Kuligowski (Principal Research Fellow (ARC future fellowship) via email erica.kuligowski@rmit.edu.au . Please do not send your application to this contact. Position Description