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Field
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implement data management and analytics protocols for clinical trial datasets Apply deep learning and AI to time series neuromonitoring data Build and test predictive models using machine learning techniques
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13 Jul 2026 Job Information Organisation/Company University of Porto Department Human Resources Department Research Field Sociology Researcher Profile First Stage Researcher (R1) Positions Postdoc
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within the digital twin environment Developing deep learning architectures for time-series forecasting, anomaly detection, and predictive maintenance of the physical asset Designing and training Physics
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(PINNs) and surrogate modelling Time-series modelling and anomaly detection Bayesian methods and uncertainty quantification Graph Neural Networks (GNNs) Spatiotemporal data engineering Digital twins and
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17 Jul 2026 Job Information Organisation/Company University of Porto Department Human Resources Department Research Field Medical sciences » Health sciences Researcher Profile First Stage Researcher
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serving the University of Chicago Booth School of Business, the Kenneth C. Griffin Department of Economics, the Harris School of Public Policy, and the Law School. For more information visit https
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Documented hands-on experience with machine learning methods, in particular for time series data Documented hands-on programming experience Fluent oral and written communication skills in English Candidates
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addresses the development of trustworthy statistical and machine learning methods for anomaly detection in such streaming data (time series), potentially extended to spatio‑temporal settings. The emphasis is
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, multimodal or multimedia systems. Directly relevant areas are preferable Documented knowledge in machine learning methods, especially hands-on experience with time series data Documented hands-on programming
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and Marine Biology conducts research on aquatic systems at high latitudes. Focusing on invertebrates, fish, and parasites, the FEG uses experimental approaches, long-term time series, and modelling