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Field
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delivery of a prototype field-deployable quantum sensing device. Support the development of project plans and schedules and participate in planning processes as required. Monitor, track and report on
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delivery of a prototype field-deployable quantum sensing device. Support the development of project plans and schedules and participate in planning processes as required. Monitor, track and report on
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This project aims to employ advanced machine learning techniques to analyse text, audio, images, and videos for signs of harmful behaviour. Natural language processing algorithms are utilized
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to peer-reviewed academic publications Qualifications Completed undergraduate degree in physics, computer science, machine learning, computational modelling, or similar. About Swinburne University
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communications from the lab a supportive, team-focused and collaborative approach to their work high level computer skills, including design software, CAD and CAM with the ability to learn, master and instruct new
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languages (C, C++, C#, Python, Matlab), experience with machine learning in robotics or computer vision, a desire to advance resilient, introspective processing architectures in robotics, a desire to work
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this role, the APPN Data Lead will supervise the APPN tech team of three (3) and coordinate the development of computer vision and deep learning tools for the APPN user community. The Data Lead will implement
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to optimise research outcomes. Advanced Data Cleaning and Analysis: Clean,engineer, prototype, and deploy statistical and machine learning models using Python and/or R to solve complex problems; maintain and
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techniques Ability to work both independently and in a multidisciplinary team Excellent organisational skills with a demonstrated capacity to meet tight deadlines and manage time effectively. Computer skills
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supervision. We operate with a commitment to high standards of care and student learning, providing the latest technology, including advanced imaging equipment like CT, endoscopy, arthroscopy, and invasive