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delivery applications. We are growing the group to comprise around six postdoctoral staff and six PhD students, forming a highly supportive and talented daily workplace. We regularly utilize large scale
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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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, including increased crop yields and improved food security. Based at the University of Adelaide, the students will learn multi-disciplinary skills, work with a vibrant team led by Dr Tatiana Soares da Costa
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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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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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, 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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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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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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children. Mechanistic modelling of disease transmission involves the use of computer code to represent the epidemic dynamics of infectious disease spread within the community. This allows modellers