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Field
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architectures Analysis and preprocessing of different data types (texts, images, time series, graphs, etc.) Review latest literature and data Orchestration and documentation of deep learning experiments
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and algorithm or approaches, and instead will have a creative approach to problem solving, exploring multiple potential techniques. Ideas will be verified on software systems (e.g. SOLIDWORKS, MATLAB
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learning, and data science, focusing on applications within the healthcare, education, and environment sectors. Designs generative AI techniques and algorithms for data integration and computational models
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student and faculty innovation and entrepreneurship that make a difference in the world. Expectations An ideal candidate will: Have a prior track record of publications at standard ML or robotics venues Be
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a variety of spectrum sharing scenarios, seeking opportunities for algorithms which provide enhanced interference resilience against different interfering systems. Develop, with colleagues, a spectrum
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, and may utilise iterative algorithms, machine learning and high-performance computing. Through the Monash Centre for Electron Microscopy, opportunities exist to acquire large experimental datasets using
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Future-Proof Smart Logistics. It aims to contribute to the realisation of the PI concept by developing advanced machine learning-based decentralised decision-making algorithms. These algorithms will enable
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systems on software defined radio (SDR) platforms and characterise them in the presence of interference in a variety of spectrum sharing scenarios, seeking opportunities for algorithms which provide
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This is a Research Assistant / Research Associate position within a 4-year long project. This position involves the development of novel Computer Vision algorithms for embedding computer vision