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scoping to delivery, while working on high-impact UNSW initiatives in research, commercialisation, and short-course development. This rare university-based role doesn’t require a PhD but calls for deep
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vision, mathematical physics, data science and quantum measurement. About the opportunity Support the development of scalable, customisable data platforms to enhance collaborative geoscience research
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, complex omics datasets (e.g. transcriptomic, genomic, proteomic), with demonstrated skills in statistical modelling; experience in machine or deep learning is advantageous. Emerging track record of research
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to assist in the delivery of research and monitoring projects across Northern Australia. The successful applicant will work closely with Traditional Owners. What you can bring to the role Possess either a PhD
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on developing and implementing seagrass restoration approaches in tropical Australia and the broader Indo-Pacific region. What you can bring to the role Possess either a PhD, or a Bachelor’s degree with a minimum
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developments like automation, predictive analytics, artificial intelligence and machine learning, allowing for increased efficiency while reducing costs and keeping employees safe. To ensure our students and are
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to detail and commitment to quality assurance. Proven proficiency in computer software packages with effectiveness, accuracy and attention to detail and an ability to learn new skills. Please Note
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health courses, ensuring high-quality, place-based learning experiences. Additionally, you will support the development of professional courses and work-integrated learning experiences, fostering evidence
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variable models (e.g., CLIP, GLIP, MaskCLIP). Knowledge of Transferability in Machine Learning is desirable. Knowledge in Active Learning is desirable. Programming skills and experience with dataset
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teaching and research portfolio. The School is at the forefront of emerging fields, including Artificial Intelligence, Machine Learning, Quantum Technologies, Energy Informatics, and Immersive Technologies