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Field
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autonomous by embedding machine learning algorithms to search through different reaction parameters Person Specification Candidates should have been awarded, or expect to achieve, EITHER: A Bachelors degree in
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modelling, enabling more cost-efficient training algorithms. Program overview The successful candidate will receive: Admission to a PhD program at the University of Adelaide; A four-year scholarship package
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Scholarship in CSIRO Industry PhD Program - Project 1: Resilient & Practical Quantum-Safe Threshold Cryptography Job No.: 678541 Location: Clayton campus Employment type: Full-time Duration: 4-year
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-based and index-based approaches, the sequent-peak algorithm, extreme value analysis, and multivariate copulas. Based on this, you will develop an improved method to map global energy drought risk and
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mapping using a team of highly mobile legged or legged-wheeled robotic platforms. The research will investigate advanced algorithms for multi-robot coordination, dynamic path optimization, and collaborative
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. They can be constrained by either compute power or memory bandwidth. This information can be used to calculate the theoretical maximum energy efficiency of an algorithm that is run on an architecture
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and empirically oriented, focusing on how political ideas, actors, and conflicts are shaped and mediated through digital platforms. Central themes may include, for example, algorithmic influence
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novel sensing approaches to combine with machine learning algorithms to solve real-world problems in food manufacturing. You will have sound knowledge in electronic engineering, embedded systems design
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well as developing solution algorithms applying mathematical and computational approaches. The group has a particular focus on automated decision making in autonomous cyber-physical systems. Autonomous systems and
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prototype/demonstrator of a low-cost smart sensor. To develop an efficient algorithm to process the vibration signals locally and to develop the firmware to be embedded within the sensor node. To validate