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doctoral researcher(PhD student) with a strong background in probabilistic machine learning, statistics, applied mathematics, computer science, or a related field, and strong programming skills, to work
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, such as computer science, neuroscience, engineering, physics, applied mathematics (or be near to completion of their PhD). Skills in computer programming (especially Python or C++ or Matlab) and
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machine learning, Computer vision, Swarms, Autonomous Robots, hardware security, and Embedded systems development is desired. The successful applicant will work on various projects on robotics and computer
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, computer science, machine learning, or natural language processing, focusing on AI for Social Good or similar. Excellent written and spoken English is required, since the project is carried out in an international
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presence in artificial intelligence (AI). This is an open search and we anticipate more than one hire. Successful applicants will have expertise in AI and machine learning and will lead independent research
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expertise in fire behaviour and climate modelling, remote sensing, and machine learning to a multidisciplinary research program that spans prescribed fire operations, fire behaviour modelling, IoT sensor
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(DFT) simulations and develop machine learning potentials to investigate zeolite-related systems. The role will focus on delivering research projects and promoting research excellence in this area. The
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. Postdoctoral applicants must hold, or be close to completing, a PhD in one of these areas. Candidates should have an exceptional academic record, a strong background in machine learning, and a robust
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Learning has an open position for a doctoral student with a background and strong interest in deep generative learning and computer vision/remote sensing. The successful candidate will join a project funded
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regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https