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statistics. We are looking for a motivated candidate, with a deep interest in mathematical statistics, with a view towards developing new methods for uncertainty quantification. Starting date no later than
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under uncertainty and decision support through combining observed data and mathematical models. The position is available from 19.08.2026 and we expect that the candidate can start the position no later
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and uncertainty. This role offers the opportunity to join a university that has placed societal impact at the centre of its new strategy, to strengthen the positive change delivered through education
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Description The Teamcore Group (https://teamcore.seas.harvard.edu) at the John A. Paulson School of Engineering and Applied Sciences (SEAS) at Harvard University seeks postdoctoral fellows to work on AI
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Control of Buildings (https://annex96.iea-ebc.org ). Responsibilities and qualifications The primary objective is to advance scalable modeling methodologies for building energy systems by combining physical
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subgroups, uncertainty sampling, as well as curriculum strategies (first general/easy, then specific/hard). appropriate aggregation metrics over the subgroups are examined (e.g., worst-group performance
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for the monitoring and prognostics of complex systems, characterized by high heterogeneity, nonlinear dynamics, and operational uncertainty. The main objective is to enhance the ability to promptly detect anomalies
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, robust, and trustworthy robotic technologies. Your research will span core challenges such as robot control, decision-making under uncertainty, multimodal information fusion, and foundational models
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datasets (e.g. ground-based radar measurements and weather station data) Contribute to the development and application of numerical models Assess uncertainties for future sea-level projections Publish
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- data modeling and assimilation towards experimental measurements under consideration of uncertainties - utilization of Explainable AI techniques to enable novel scientific discoveries - explore and