284 parallel-and-distributed-computing-phd-"https:" Fellowship positions in Australia
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-career or emerging researcher to contribute to cutting-edge work in: Multiagent systems and distributed control Learning and optimisation Variable structure and sliding mode control Smart power and energy
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opportunity for an early-career or emerging researcher to contribute to cutting-edge work in: Multiagent systems and distributed control Learning and optimisation Variable structure and sliding mode control
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opportunity for an early-career or emerging researcher to contribute to cutting-edge work in: Multiagent systems and distributed control Learning and optimisation Variable structure and sliding mode control
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and experience: Qualifications PhD in Computer Science, AI, Machine Learning or related field Experience A strong research track record relative to opportunity, including the ability to produce and
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produce high quality outputs. To be successful in this position, you will have: PhD in Tissue Engineering, Biomaterials, Biomedical Engineering, Cell Biology or related field. Experience in tissue
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quantitative modelling of energy systems, such as power system analysis, techno‑economic modelling or distributed energy resource studies. Demonstrated experience with computational modelling and programming in
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community and thrive in this role, you will likely have the following skills and experience: Qualifications PhD in Computer Science, Engineering, or related discipline Strong publication record in top-tier AI
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in human induced pluripotent stem cells (hiPSCs)-derived skin organoids (https://pubmed.ncbi.nlm.nih.gov/38044307/ ), and the generation of vascularized skin organoids (https
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on Australia’s population size and distribution, labour force composition and housing demand. You will join a collaborative and energetic research team of demographers and economists, working closely with
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medicine. This nationally recognised program aims to advance fundamental understanding and translational applications within the discipline. Funded by the Australian Research Council Discovery Project