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analysis and data processing. Strong programming skills in R (preferable) and/or Python, and experience or interest in weather prediction or climate models. Knowledge of machine learning, AI techniques, and
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government background checks (allow for between 4 to 8 weeks) and complete any other CSIRO requirements. Selection criteria To be eligible applicants must: Have a basic understanding of machine learning
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microfluidic fabrication and experiments 3D printing machine learning. Demonstrated programming skills (Matlab, C++, or Python). Desired Demonstrated ability to work independently and to formulate and tackle
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to peer-reviewed academic publications Qualifications Completed undergraduate degree in physics, computer science, machine learning, computational modelling, or similar. About Swinburne University
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, Engineering or others related to the PhD topic) Excellent programming and/or robotics background, with a keen interest in human-robot interaction Prior knowledge of robotics and machine learning (e.g., relevant
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the energy market, Role of EVs in the grid, Power System Stability Analysis Using Machine Learning Techniques and more. Eligibility Requirements: Applicants must be Australian citizens or Permanent Residents
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fairness, privacy and legal guarantees for ADM systems, such as recommender and machine learning based systems. It takes a multi-disciplinary approach and although focused on the transportation focus area
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computer vision and machine learning methods to interpret the photovoltaic (PV) solar farm's condition and perform various inspections and anomaly detection. The research will draw from state-of-art
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The successful applicant will conduct research to design and develop novel machine/deep learning based trust technologies for securing IoT services/devices. The successful applicant will conduct
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Building tools to detect or prevent unsafe AI outputs Exploring regulatory gaps and proposing solutions This is an ideal opportunity for candidates with interests in machine learning, public health, ethics