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: Develop novel machine learning theories and techniques for analyzing noisy time-series data, with a particular focus on seismic signals Perform uncertainty quantification in time-series analysis to assess
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and the Environment is a centre for experimentation and excellence in the financial solutions needed for a just transition to a net zero and nature positive economy. The Lab seeks to appoint up to two
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We are seeking for a full-time Postdoctoral Fellow to work on projects in the area of household finance, investment, and financial literacy. The project is part of a large 5-year research program
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Job Description Job Alerts Link Apply now Job Title: Postdoctoral Fellow (Household Finance & Financial Literacy) (28302) Posting Start Date: 24/03/2025 Job Description: Job Description We
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Job Description Job Alerts Link Apply now Job Title: Research Analyst/ Associate/ Fellow in Financial Valuation and Analysis Posting Start Date: 19/09/2024 Job Description: The Role The Sustainable
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Voices, is offering an exclusive scholarship for a participant to represent Australia and attend the IMF and World Bank this October. About the IMF/WB Annual General Meeting The IMF/WB Annual Meetings
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or domain-specific time-series (e.g., financial, medical) Experience with open-source contributions or system/toolkit development More Information Location: Kent Ridge Campus Organization: School of Computing
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and statistics, with expertise spanning time series analysis, Bayesian inference, financial econometrics, and data analytics. As home to one of the strongest forecasting research groups worldwide, we
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warning and action. You will be using both time-series and longitudinal Cholera surveillance data along with external data on contributory factors (environmental, demographic, socio-economic) to develop
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 2 months ago
uncertainty with applications in multi-robot domain. We will explore Integrated Planning & Learning and Reinforcement Learning in non-deterministic and partially-observed scenarios. The methods will be