15 software-defined-network-phd Fellowship positions at University of Adelaide in Australia
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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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, epigenetics, development, and cell biology to lead and contribute to cutting-edge research. To be successful you will need: A PhD in Cell Biology, Molecular Biology, Genetics, Biochemistry, or a related area
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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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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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fundamental and demand-driven research on modelling and analysis of complex social networks. This line of research is broadly focused on modelling, analysis and estimation of complex network models in
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environment. This includes work undertaken within our invaluable Terrestrial Ecological Research Network . To be successful, you will need: A PhD in marine/coastal ecology or a related discipline. To be
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combatting wildlife trafficking and environmental harm. ESSENTIAL MINIMUM CRITERIA PhD in a relevant discipline such as computer science, data science, digital forensics, cyber security or a related field with
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will need: A PhD or equivalent in stochastic modelling, data science, network analysis, statistics, or related discipline Is eligible to apply for an Australian Government security clearance. Research
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Canada, the USA, the UK, or New Zealand. Proficiency in Python, MATLAB, or C++, and demonstrated experience in deep neural networks and mathematical optimisation, are essential. A commitment to equity
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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