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contribute to groundbreaking projects in OP-MEG and Bayesian computations. This role offers you the chance to collaborate with leading researchers, mentor students, and shape the future of cognitive
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to engage with multidisciplinary teams and external partners. Desirable attributes include experience with spatio-temporal models, machine learning, Bayesian methods, and knowledge of environmental exposure
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. Your expertise includes machine learning techniques such as Bayesian optimisation, and you’re comfortable working with experimental data, high-performance computing environments, and (ideally) thin film
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. An understanding of and commitment to UNSW’s aims, objectives and values in action, together with relevant policies and guidelines. Knowledge of health and safety responsibilities and commitment to attending
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management decisions and mitigate risk. The successful candidate will develop the research objectives in collaboration with an experienced supervisory panel, comprised of researchers at the University
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exciting opportunity to conduct independent research, under the support and guidance of more senior academic staff, within the field of environmental analytical chemistry. A major objective of these projects
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effective relationships. Evidence of highly developed interpersonal and organisational skills. An understanding of and commitment to UNSW’s aims, objectives and values in action, together with relevant
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research as part of a team, focusing on publication, conference presentations, and securing research funding. Contribute to and assist with the implementation of the strategic and operational objectives
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approaches. Operating under broad direction, you will translate research objectives into specific experimental and analytical tasks, acting as a subject matter expert on methodological approaches and providing
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models, multi-object tracking, and post-processing methods to improve traffic video analytics in complex environments. Drive benchmarking, evaluation, and deployment optimisation of AI models, ensuring