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discipline knowledge and developments. Demonstrated track record in research with outcomes of high quality and high impact with clear evidence of the desire and ability to continually achieve research
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data. Track record of disseminating research findings (e.g., publications, conference presentations). Strong communication skills and the ability to work collaboratively in a team environment. Desirable
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Fellowships are open to candidates from all countries and all creative and performing arts disciplines. Applicants will have a track record of proven academic excellence and will have already made significant
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all countries and all creative and performing arts disciplines. Previous awardees have included musicians, composers, writers, dancers, film makers and photographers. Applicants will have a track record
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focused on the challenge of accelerating ternary neural networks using FPGA devices. The successful candidate will have significant experience in machine learning, FPGA design and an outstanding track
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and Ar-Ar geochronology, fission-track and (U-Th-Sm)/He thermochronology, vitrinite reflectance, and thermal history models. New relational data models data for incorporating methods such as include
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mission is to accelerate the commercialisation of research for the Australian Defence Force (ADF), develop education training pathways, fast-track entrepreneurs' ideas to commercialisation, and enhance
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ternary neural networks using FPGA devices. The successful candidate will have significant experience in machine learning, FPGA design and an outstanding track record in conducting machine learning research
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including word processing (MS word), spreadsheets (MS Excel), and statistical analysis packages An understanding of and commitment to UNSW’s aims, objectives and values in action, together with relevant
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fish sampling, baited remote underwater video and acoustic tracking. These data will be used in a metapopulation modelling context to better predict the effects of habitat modifications and loss