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mathematical concepts such as optimization, linear algebra, probability, and statistics, relevant to AI and quantitative modelling. Technical proficiency in programming66: Demonstrated programming skills with
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automated recovery algorithms, improving system resilience. Research Areas for Master’s and PhD Students AI-Enhanced Resource Forecasting and Optimization: Research Focus: Developing and testing ML algorithms
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multi-disciplinary teamwork amongst staff for optimal clinical service outcomes Involvement in continuing professional development activities Attendance and participation in the clinical meetings
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. This role involves collaborating with educators and program leaders to ensure compliance with RMIT policies and TEQSA requirements while developing optimal pathways for students. Key responsibilities include
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 2 months ago
research challenges in: dynamical systems differential games optimal control numerical optimisation and/or machine learning in control About the opportunity The successful applicant will become part of a
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optimal growth conditions for the button mushroom. This research explores the role of specific micro-organisms in the composting process, how they interact with the growing button mushroom mycelium, and how
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Australian National University | Canberra, Australian Capital Territory | Australia | about 2 months ago
, Information, Intelligence, Communications, Automation, Decision, and Autonomy (CIICADA) Lab where we explore innovative research challenges in: dynamical systems differential games optimal control numerical
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Responsible for developing and maintaining optimal resource utilisation models that align academic timetabling with the strategic direction of the University. • Fed Services – Berwick, Churchill
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Professional Services. The position manages the operation of complex administrative and technical functions encompassing the delivery of student, academic and operational services; optimal planning and
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research often overlooks the complexities of mixed-vehicle environments, and the development of optimal deployment, routing, and charging strategies. This project aims to address these gaps by optimising