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publication track record in relevant areas of high-energy astrophysics in leading academic journals. A strong interest in and commitment to the delivery of quality undergraduate education. Experience in and/or
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prediction, signal tracking, fluid dynamics, and space exploration. Advancing Signal Modelling with Physics-Informed Neural Networks This project aims to develop Physics Informed Neural Networks (PINNs
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field. They will possess a demonstrated track record of high-quality research, including publications in leading journals and conferences, particularly in the area of electrode/electrolyte interface
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meet deadlines, with flexibility to alter priorities to meet changing demands. An emerging research track record with evidence of recent high quality scholarly publications. Demonstrated capacity to work
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AI/ML for Object Tracking and Sensor Fusion, you will develop next-generation algorithms that power intelligent aerial systems—enabling real-time object tracking, multi-sensor data fusion, and
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skills in R and Python. Demonstrated experience with the handling and maintenance of crops in field-based and controlled environments, and genetic transformation of cereal crops. A strong track record of
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proven track record as a reliable and trusted team player. They can conduct research and engage with stakeholders to build effective working relationships. They are able to comply with obligations
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track record of peer-reviewed publications and conference presentations in relevant fields. Ability to work collaboratively in interdisciplinary teams and communicate clearly and effectively in English
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, diversity and inclusion, and ability to contribute to the diversity of the School of EME community Desired Characteristics: Track records of scholarly publications in prestigious journals, as measured by Q1
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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