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Job no:517690 Work type:Fixed term - Part-time Campus:Adelaide Categories:Level B, Faculty of Arts, Business, Law and Economics (Level B) $114,917 0 $135,932 per annum plus an employer contribution of 17% superannuation applies. Fixed term part-time (0.8 FTE) position for 1 year. This position...
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This PhD scholarship is funded by an Australian Research Council Industry Fellowship grant. It is a 3.5-year research training program. The ARC Industry Fellowship program aims to develop a strong
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-based health care. High level interpersonal, communication and organisational skills. Ability to contribute to a diverse and collaborative team environment. Commitment to ongoing learning. Level B: PhD in
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the molecular mechanisms that enable male germline recovery following damage by genotoxic drugs, and the regenerative responses of SSCs. The research will use in vivo models, organoids, SSC culture, and genomic
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need: A PhD in epidemiology, public health, medical sciences or other areas relevant to primary health care Demonstrated experience contributing to the coordination of quantitative health research
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Criteria: A PhD in applied mathematics, engineering, computer science, data science, physics, or a related area. Strong academic track record (including peer-reviewed publications and conference
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: A PhD in Mathematics, Computer Science, Engineering or other Machine Learning-related field. Programming experience in MATLAB, Python, C++ or other relevant language and experience in deep neural
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Job no:517434 Work type:Fixed term - Full-time Campus:Adelaide Categories:Level A, Level B, Faculty of Sciences, Engineering and Technology (Level A) $81,293 - $109,307 (Level B) $114,917 - $135,932
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Job no:517322 Work type:Fixed term - Full-time Campus:Adelaide Categories:Level A, Level B, Faculty of Sciences, Engineering and Technology (Level A) $81,293 - $109,307, (Level B) $114,917
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PhD in Computer Science, Engineering or other Machine Learning-related field. • Programming experience in python, C++ or other relevant language and experience in deep neural networks • Strong