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research interests in one or more of the following subfields: scientific machine learning, optimization, deep learning, uncertainty quantification, (Bayesian) inverse problems, reduced order modeling, high
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inverse problems is also desirable. Application Requirements A complete application consists of: Zintellect Profile Educational and Employment History Essay Questions (goals, experiences, and skills
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Job Reference: 812682 About the Role: In this role, you will contribute to several collaborative projects between Curtin University, industry and research partners. You will primarily contribute
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Position Description The successful candidate will work on using satellite observations of atmospheric methane to better quantify methane emissions on regional to global scales through inverse analyses