Job Description:
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We are seeking a highly motivated and skilled researcher to join our team in the field of statistical machine learning. The successful candidate will have the opportunity to work on cutting-edge research projects, collaborate with international experts, and contribute to the development of innovative solutions for real-world problems.
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About the Project:
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This PhD project focuses on developing new methodologies and algorithms for statistical learning, with applications to metocean and ocean engineering. The research will involve sequential decision making, data-driven spatio-temporal inference, and statistical analyses of complex ocean dynamic processes.
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Required Skills and Qualifications:
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To be considered for this position, applicants should hold an Honours undergraduate degree or a Masters degree in Statistics, Machine Learning, or a closely related field. The ideal candidate will have strong mathematical and programming skills, excellent communication skills, and a passion for using statistical learning to model and predict environmental phenomena.
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Benefits:
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The successful applicant will receive a generous scholarship to fund their studies for three years full-time. An additional top-up scholarship is available for outstanding candidates. Tuition fees for outstanding international students will be waived.
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Application Process:
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Applicants should submit their academic transcripts, CV, and a cover letter outlining their motivation for conducting research in this area. For informal queries, please contact A/Prof. Andrew Zammit Mangion, A/Prof. Edward Cripps, or Prof. David Leslie.
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Statistical Learning