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Field
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networks. The research will employ mathematical modelling and computer simulation to identify synaptic plasticity rules which enable effective learning in large and deep networks and is consistent with
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/C++; hands-on experience with deep learning libraries (e.g., PyTorch) 5. Ability to organise and prioritise work to meet deadlines with minimal supervision 6. Strong written and verbal
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journal publications dependent on your background discipline(s) and should hold sufficient theoretical knowledge of deep learning-based methodologies as well as working with real-world data. Informal
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(KCL, London, UK) but will also have the opportunity to travel and work at the Centre for AI and Machine Learning (ECU, Perth, AU) and the School of Psychiatry and Clinical Neuroscience (UWA, Perth, AU
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require a deep understanding of the classical infrastructure that supports them, including analog control systems. As quantum devices scale toward the million-qubit regime, modeling these complex systems
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. For this multidisciplinary project, we are looking for a highly motivated cell biologist who holds a PhD in a relevant field with a commensurate publication record. We welcome applications from candidates with a background in
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on qualifications and relevant skills acquired and will also be determined by the funding available. About you Applicants will hold a PhD/DPhil or be near completion of a PhD/DPhil in a subject relative to Structural
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analysed by bespoke machine-learning driven algorithms, combined with physical models, to de-noise images, identify features and correlate properties, giving critical insights into power loss pathways
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be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD qualified in relevant subject area (or pending results) Proven experience
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and experience: Essential criteria PhD qualified in relevant subject area (or pending results) Proven experience in managing research projects within healthcare or educational settings, including