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Field
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related to robotics, robot operating system (ROS), system engineering, computational mathematics, C/C++ programming, data structure and algorithm, artificial intelligence (AI) and machine learning
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learning, machine learning algorithms, and statistical modelling Ability to interpret complex data, derive insights, and optimize machine learning solutions. Skills/Attributes: Strong communication skills
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. Assess the build quality of parts generated through control model algorithms. Validate that methodologies developed are transferrable between different LPBF platforms through evaluation of parts generated
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decision with multiple data sources. One example is to develop the semi-supervised methods and dynamic system interfacing algorithms to produce an automated and real-time information exchange across
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hardware-in-the-loop (HiL) techniques and ML algorithms for the accurate and on-time detection of faults, so that failures can be prevented by alerting the end-users and diagnosticians during periodical
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candidate will develop machine learning and algorithmic design skills. The candidate will gain valuable multidisciplinary skills in the area of machine learning and data analytics methods and their
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communications and sensing. Skills Essential: C1 Excellent programming, algorithm development and scripting skills C2 Research creativity and strong cross-discipline collaborative ability as appropriate C3
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novel contributions to the field of computer vision and deep learning in smart manufacturing. These novel algorithms will then be integrated on to a mobile robotic system that will inform the design and
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our software development team, developing novel scientific algorithms and applications in the areas of spectroscopic analysis and mining of the science data catalogues extracted from the pipelines
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information from high-quality videos that share content with distorted footage as constraints in the learning process of modelling algorithms. This method uses the characteristics and knowledge embedded in high